chandra prakash agrawal - virginia tech · chandra prakash agrawal joseph r. loferski, chairman...

. iiFULL-FIELD DEFORMATION MEASUREMENT IN WOOD USING DIGITAL IMAGE PROCESSING

bvChandra Prakash Agrawal

August 18, 1989

Blacksburg, Virginia i

FULL-FIELD DEFORMATION MEASUREMENT IN WOOD USING DIGITAL IMAGE PROCESSING

bvChandra Prakash Agrawal

Joseph R. Loferski, Chairman

Wood Science and Forest Products

(ABSTRACT)

A digital image processing system was used to non-destructively measure the full-

field deformation on aluminum and wood specimens Ioaded in compression and

bending. The measurement technique consisted of creating a random speckle pattern

on the specimen surface, recording images before deformation and after deformation,

and computing the relative displacements of small image subsets. Two methods for '

producing speckle patterns on the specimens were studied: spray paint and

adhesive-backed photographic film.

Baseline tests were conducted to evaluate the influence of signal noise on the

measurement system. Uniform translation tests were conducted to evaluate the ca-

pability of the system for measuring finite motion. the technique was used to monitor

the full-field deformation response of aluminum and wood specimens tested in4

bending and static compression. Moderate duration compression creep tests were

conducted on the wood specimens to investigate the suitability of the system for

monitoring the creep response of materials. The results obtalned from the two

speckle techniques were also compared. The results showed that for the magnifica-

tion and speckle patterns tested displacement measurements smaller than 3.29x10·‘I

inch may be unreliable due to signal noise.

The digital image processing technique was shown to be a useful laboratory tool for

measuring full-field displacements on the surface of the materials under stress. Full-

field strains can be derived from the measured displacements. The

displacement/strain measurement technique may be applied to many problems as-

sociated with understanding the mechanical behavior of wood such as stress con-

centrations, verification of analytica! models, and even for non-destructive structural

evaluation of existing buildings.

II

„ ‘ IIIII

Acknowledgements

Acknowledgements ‘ iv

I

Lastly, I wish to express my gratitude to Dr. Geza Ifju for the constant encouragement

I received from him in pursuing the research work. '

IIII

Acknowledgaments v

|

Table of Contents

1.0 INTRODUCTION ............._........................................ 1

1.1 Objectives ......................................................... 2

1.2 Limitations of Conventional Techniques ................................... 3

1.3 White-light Speckle Method ............................................ 5

1.4 Overview ....................................’...................... 6

2.0 LITERATURE REVIEW ................................................. 8

2.1 Initial Studies ...................................................... 11

2.2 Digital Correlation Technique .......................................... 13

3.0 THEORY .......................................................... 16' 3.1 Object Deformations ................................................ 16

3.2 Strain ............................................................ 20

3.3 Reconstruction of Digitally Recorded lntensity patterns ...................... 23

4.0 EXPERIMENTAL MATERIALS .......................................... 26

4.1 General .......................................................... 26

Table of Contents vi

4.2 Hardware .........................................................274.3

Software ......................................................... 29

· 4.4 Speckle Patterns ................................................... 30

4.5 Lighting Arrangement and Camera Mount ................................ 34

4.6 Specimens ........................................................ 36

4.7 Testing Machines ................................................... 36

5.0 EXPERIMENTAL PROCEDURES, RESULTS AND DISCUSSION ................. 38

5.1 Baseline Test ...................................................... 39

5.2 Uniform Translation Test ............................................. 42

5.3 Bending Test ...................................................... 45

5.3.1 Aluminum Beams.................................°.............. 48

5.3.2 Wood Beams ................................................... 51

5.4 Compression Tests ................................................. 54

5.4.1 Aluminum Block................................................. 55

5.4.2 Wood Blocks: ParaIleI~to·grain ...................................... 57

5.4.3 Wood Block: Variable grain angle ................................... 62

5.4.4 Wood Block with a Knot ........................................... 63

5.5 Creep Tests ....................................................... 70

6.0 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE RESEARCH . . 77

6.1 Summary ......................................................... 77

6.2 Conclusions ....................................................... 80

6.3 Recommendation for future work ....................................... 81

7.0 REFERENCES ...................................................... 82

Appendlx A. DESCRIPTION OF STRAIN TENSOR FORMATION .................... 87

Table of Contents vii

11

A.1 Subscripts ........................................................ 87

A.2 Differential Length .................................................. 88

Appendix B. NUMERICAL PROCEDURE FOR DEFORMATION ANALYSIS USING DIGITAL

IMAGE CORRELATION .................................................. 89

B.1 Background ....................................................... 90

B.2 Iterative Method ................................................... 94

Appendix C. DESCRIPTION OF MATROX6 SOF'I’WARE ........................... 97

Vita ................................................................ 103

111111

Table of Contents vül :1' 11

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I I IList of Illustrations III

Figure 1. White-light speckle pattern and Young’s fringes on a wood block [15]. ....... 4

Figure 2. The Longitudinal, transverse and radial directions in a wood block. ....... 10

Figure 3. Gray—|evel representation of undeformed and deformed digital speckle images[26]. ....................................................... 17

Figure 4. Deformation of a body. ......................................... 19

Figure 5. A typical array of digitized intensity pattern. ......................... 24

Figure 6. Schematic representation of the experimental set-up. .................. 28I

Figure 7. Speckle patterns on wood specimen and their histograms ............... 34

Figure 8. The camera arrangement showing the video camera, Oriel mounting unit andthe circular tubelight. .......................................... 35

Figure 9. Results obtained from translation test at 3 magnitication levels ........... 46

Figure 10. Testing arrangement for bending test ............................... 47

Figure 11. Comparison of displacements of aluminum beam bending, span = 12 inch . . 49

Figure 12. Comparison of displacements of aluminum beam bending, span = 10 inch . . 50

Figure 13. Comparison of displacements for wood beam bending. Yellow-poplar, span =14 inch ..................................................... 52Figure 14. Comparison of displacements for wood beam bending. Southern yellow pine

beam, span = 14 inch ......................................... 53

Figure 15. Loading direction displacements ofthe aluminum block in compression .... 56

Figure 16. Transverse displacements of the aluminum block in compression ......... 58

Figure 17. Loading direction displacements of Southern pine block incompression-parallel-to-grain.............................................. 60 I

Figure 18. Transverse direction displacements of Southern pine block in compression- Iparallel-to-grain ......................................._....... 61 I

I· IList of Illustrations ix I

I

I_ I

II

Figure 19. Displacements of Southern pine block in compression-30°—to-grain ........ 64

Figure 20. Displacements of Southern pine block in compression·45°-to-grain ........ 65

Figure 21. Displacements of Southern pine block in compression-60°-to-grain ........ 66

Figure 22. Displacements of Southern pine block in compression-90°—to-grain ........ 67

Figure 23. Effect of grain angle on compliance of wood in compression in the loading di-rection ..................................................... 68

Figure 24. Effect of grain angle on compliance of wood in compression in the transversedirection .................................................... 69

Figure 25. Compression parallel·to-grain in loading direction in Southern pine block witha knot ...................................................... 71

Figure 26. Creep in a Southern pine block in the loading direction - compression parallel- _to·grain at 50% of the estimated ultimate load . ._..................... 73

Figure 27. Creep in a Southern pine block in the transverse direction · compressionparallel—to-grain at 50% of the estimated ultimate load ................. 74

Figure 28. Creep in a Southern pine block in the loading direction · compression parallel-to-grain at 75% ofthe estimated ultimate load ....................... 75

Figure 29. Creep in a Southern pine block in the transverse direction - compressionparallel-to-grain at 75% of the estimated ultimate load ................. 76

Figure B.1. Local Distortion of a Subset Image [26]. ............................ 91

Figure B.2. Deformation ofa Subimage in a Sampling Grid [26]. .................. 96

Figure B.2. Flow diagram for correlation routine [26]. . ._........................ 92

List of Illustrations x

I

List ef Tables I

Table 1. Baseline test on photographic tilm speckle and spray paint speckle ........ 41

Table 2. Baseline test with image averaging ................................. 43

. I

List of Tables . xl ;

l

1.0 INTRODUCTION

Wood is a natural material and its mechanical properties are highly variable among

species, within species, and even within an individual board. Due to its complex

internal structure wood is characterized as an anisotropic, porous, and inhomogene-

ous material. Experimental stress analysis of wood is complicated by the great vari-

ety of species, the variabillty of the material, the continually changing conditions of

supply, and the many factors affecting test results, such as moisture content and load

duration [56]. Designing safe and economical timber structures requires material

property data and accurate analysis procedures. ln contrast to metals, determining

any wood property to a satisfactory confidence level requires a large sample size and

a statistically valid sampling scheme. Recent advances in structural analysis meth- 4

ods, in concert with advances in computer technology, have produced complex ana-

lytical models for predicting the behavior of structures. The evident question is : How

accurate are these models when applied to a material as complex as wood? Exper-

imental verification is generally used to evaluate the accuracy of analytical pred-

ictions. Such verification requires measuring the material properties of each member

INTRODUCTION 1ll

· . 1l° l

for input to the analysis model, and measuring, the displacements and strains of the lstructural members for comparison to the analytioal predictions.

Many existing methods for displacement measurement can be used to compute the

average strain at a point in the member. Full-field deformation data would be useful

for verification of analytioal models. Practical methods for measuring the full field

deformation and strain in wood members are lacking. The objective of this study is

to investigate the suitability of digital image processing for full field deformation

measurement in wood members. ·

1.1 Objectives

· The objectives of this project are :

• To investigate the suitability of digital image processing for full-field deformation

measurement In wood.• To apply this technique to gain Insight into the mechanical/physical behavior of

wood under compression.

The digital image processing technique involves acquiring and mathematically proc-

essing video images of an object before deformation (called the undeformed image)

and after deformation (called the deformed image). A video camera is linked to a

computer through an image grabbing board. The images captured before deformation

and after deformation are digitized and stored on a disk. A computer program ana- jlyzes the images and computes the relative displacements of small subsets of the z

liN‘rRo¤uc‘rIoN 2 Il

1

1Z

digitized image. The displacements can be used to compute the full-field strain on the ldeformed object surface. i1.2 Limitations of Conventional Techniques :

Dial gages, strain gages, or linear variable differential transducers (LVDT) are the

ccnventional devices for measuring the strain in wood structural elements. Since

these devices measure strain over a limited gage length they may miss the critical

regions of strain that may occur elsewhere in the member. _

The electrical resistance strain gage is commonly used for measuring strain in wood',

but the errors introduced by reinforcement effects, transverse sensitivlty, thermal ef-

fects, etc., [48] reduce its suitability. Moreover, full-field strain measurement requires

placing many strain gages on the specimen surface, reducing its applicability for

full—field strain measurement. l

Holography, moire interferometry, and photoelastic coatings are optical techniques

used extensively for measurement of full-field strain, on metals, on composites, and

to a limited extent on wood [37]-[38]. The photoelastic method has been in use since

1912 [55], but it requires duplication or coating of the specimen with a photoelastic

material. The high cost of the process restrict the methods to relatively small mem-

bers and few replications.

Moiré interferometry works on the principle of interference of an undeformed refer- Eence grating and a deformed specimen grating. lt’s disadvantage is the difficulty of1

INTRODUCTIGN 3

replicating the grating on the specimen surface. Holography offers the maximum

sensitivity in strain measurement but also has limitations. For example, stability re-

quirements and localization of fringes (a type of parallax [53]).

The laser speckle method photographically records the speckle pattern which is re-

flected from the surface of the object when it is illuminated with coherent light. A

speckle pattern is created when reflected coherent light produces a random intensity

pattern. Correlation between the undeformed and deformed surface speckle patterns

gives the strains and displacements.

All the optical techniques described above are based on coherent-light optical sys-

tems. These systems are plagued with artifact noise which severely limits their ap-

plication. Also, the coherent-Iight sources are generally expensive, and the coherent

optical signal processing environment is usually stringent. For example, it requires

a dust-free room and a heavy optical bench [2]. The data processing required to re-

duce the fringe patterns to displacements, is laborious and time consuming.

1.3 White-light Speckle Method Z

ln the white-light speckle method a white-light source is used, (e.g., projector bulb

or flash bulb) instead of laser light. lt is called white-light because it consists of most

of the spectrum of visible light. White-light does not have the "noise" problems of

laser light. An important noise source in an optical signal processor is the random

defects in the input. These defects get suppressed when a broad spectrum light

lNTRoDUcTION 5

l

l

source is used [2]. Digital correlation techniques coupled with white-light speckle is l

a versatile technique and has been applied in many fields of study [13-19,21-32].

Digital image processing combined with the white—light speckle technique offers a T

unique combination of high sensitivity, excellent contrast, range, and spatial resol-

ution to study the behavior of wood at the micro- and macro-scopic levels. This

technique may also offer an experimental counterpart to the powerful computational

methods of solid mechanics, where displacement fields are the primary output. The

experimental measurements also provide data to evalu_ate the results of computa-l

tional programs. The technique can be used to verify finite element models [39].

The displacement/strain measurement technique may be applied to many problems

associated with the mechanical behavior of wood including stress concentrations,

stress intensity measurements, computation of in-situ strains in a structural member,

and even for non-destructive structural evaluation of existing buildings.

1.4 Overview

Chapter 2 contains review of literature related to digital image processing, a dis-

cussion of wood characteristics, and an introduction to displacement measurement

with the speckle technique.

Chapter 3 discusses the theoretical formulation of displacements, strains and a cor-

relation algorithm developed to compute full-field displacements from video images.

INTRODUCTION 6 }l

. l

Chapter 4 contains details of the experimental techniques, including the hardware

and software systems and coating techniques to produce random speckle patterns

on the specimens. Chapter 5 contains details of the tests conducted to verify the

digital image processing method. The experimental results are also discussed in

chapter 5. Chapter 6 contains a summary and conclusions of this work and rec-

ommendations for future research.

lNTRODUcTl0N 7

l l

2.0 LITERATURE REVIEW

To measure full-field deformation and strain in wood members, it is necessary to

understand its basic cellular structure.

8 Wood is composed principally of carbon, hydrogen, and oxygen. These chemlcal

constituents are comblned into three organic polymers: cellulose, hemicellulose, and

Iignin. Cellulose constitutes almost 50% of the weight of the wood. Cellulose conslsts

of glucose units arranged as a linear polymer. Hemicellulose is a branched polymer

of six -carbon and five-carbon sugars. Lignin is a complex and high molecular weight

polymer built upon phenylpropane units. Lignin is not a carbohydrate but phenolic in

nature.

Wood cells are formed from these three polymers. In the cell wall, long, chainlike

molecules of cellulose form into bundles and are Iaid parallel to each other. These

cellulose bundles are then surrounded with hemicellulose and form larger units

called microfibrils. Cell walls are made of mlcrofibrils Iaid down in layers. Lignin ls

deposited between microfibrils. The cell wall conslsts of inner Iayers called second-

LITERATURE REVIEW 8

ary wall enclosed in the primary wall. The secondary wall is divided into three layers

called ST, S2, and S,. The microfibrils are oriented in different directions in the three

layers.

The wood cell has a hollow center (lumen), is closed at the ends, and ls perforated

with openings called pits. Most of the cells found ln coniferous wood (softwood) are

tracheids, which comprise 90% to 95% ofthe volume ofthe wood. Tracheids are cells

about 100 times longer than their diameter. The functions of conduction and support

of the tree are carried out by the nonllving tracheids. Other type of cells found in

softwood are rays. The rays in softwood are narrow and they provide conduction in

radial direction. Rays also have effect on wood properties, for example, they restrain

dimensional change in the radial direction. The cell structure of hardwood ls very

complex. The fundamental difference between softwood and hardwood is that

hardwoodsl contain a type of cell called a vessel element [65]. .

The seasonal nature of growth of a tree is characterized by growth rings as shown in

Figure 2.

The cell wall composition and orientation in addition to cell bundling makes wood

inhomogeneous and anisotropic. There have been several models proposed to char-

· acterize the load-deformation behavior of wood but none can describe all the loading

conditions. Wood is modeled with Iongitudinal (L), radial (R), and tangential (T) axes

as shown in Figure 2. This modeling leads to 12, elastic constants (3 elastic modulii

EL, ET, and ER , three shear modulii GTR, GRL and GTL and 6 Poisson’s ratlos). Measure-

ment of these elastic parameters is difficult because of inhomogeneity and high vari-

ability in the material and is an important area of research.

LITERATURE REVIEW ‘ 9

2aI2.1 Initial

StudiesAlthoughthe phenomenon of speckle is most often associated with the "twinkIing"

appearance of objects illuminated with a laser, the history of speckle, or speckle like

phenomena predates the invention of the laser by well over 100 years [1]. The trou-

blesome effects of laser speckle in holography spurred study of the white-light

speckle methods and eventually brought it to the stage of practical utilization. The

monograph "Speckle Metrology" [1] gives a description of various speckle techniques

and applications.

Because of relative advantages of white light, many scientists experimented with the

white-light speckle technique. The first study in 1972, was on metrology application -

for surface roughness measurement [3]. Subsequently the theory of partially coher-

—ent, polychromatic speckle for surface roughness measurements was developedl

[41-[BL

The major advantages of a white-light system for displacement/strain measurements

are [2]: _

1. It is capable of suppressing the coherent artifact noise;

2. The white-light source is generally inexpensive;

3. The processing environment is not very stringent;

4. The white-light system is easy and economical to maintain; and

5. lt is suitable for color signal or image processing.F

LITERATURE REVIEW 11 Fl° ll

Boone and De Backer [9] applied the white-light speckle technique to strain meas-

urement. The expense of the laser technique was the motivation for investigating

white-light speckling. They performed experiments using surface paint, retro-

reflective paint, surface texture, and light transmission through transparent objects.

The basic phenomena occurring in all the experiments was Young’s fringes. Boone

and De Backer’s [9] work has direct relation to wood research, because it demon-

strated that surface texture can be used to construct Young’s fringes. In one exper-

iment [9] a reinforced concrete cantilever beam coated with speckle pattern was

subjected to a bending moment and a double exposure photograph was made of the

initial and deformed states. The resulting Young’s fringes gave excellent correlation

with theoretical results.

Burch and Forno [10] used a high sensitivity l\/loire grid technique to study deforma-l

tion in large objects. However the method could not convert the data into corre-

sponding x-, y- and z- displacements of the object.

Chiang and Asundi [11] studied the white-light speckle method using a camera lens

that was not "tuned" to a particular frequency. They observed that the uneven dis-

tribution of the beads results in a speckle pattern with a spatial frequency content

much wider than that covered by the range of bead sizes. When recorded by double

exposure, the white-light speckles behaved like laser speckles in that Young’s fringes

representing the displacement vector were generated upon Fourier transform of the

resulting specklegram.

In a later paper Burch and Forno [12] reported new applications of a high resolution

white-light speckle technique. They used this technique to analyze out-of-plane vi-

bration of a car door.

LITERATURE REVIEW 12

l

Chiang and Asundi [13]-[15] developed the theory of white light speckle method. They

also demonstrated its appllcability in different types of measurements including in-

plane displacement, 3-dimensional displacement, interior displacement, and large

deformation measurement. They also investigated ways of improving the sensitivity

of the technique.

2.2 Digital Correlation Technique

All the techniques discussed previously suffer from a basic disadvantage : they em-

ploy coherent light to Fourier transform a double exposure specklegram to obtain

Young’s fringes, and therefore, they are not truly white light speckle methods.

Recently researchers developed a digital image processing tool for measuring dis-

placements and strains from the surface of an object coated with a speckle pattern.

The first experiment was reported by Peters and Ranson [21] in 1982. They correlated

the reference and deformed speckle images (mathematically similar to area corre-

lation [20] in pattern recognition) to obtain full-field displacements of an object’s sur-

face. This method uses a computer system to cross-correlate a reference scene

made by a video camera and stored as digital image, with a digital image photo-

graphed after the specimen was deformed by an applied stress. Extensive math-

ematical techniques have been developed for correlating a reference scene with a

stored image in references [21],[34] and [35]. An important result shown by [21] was

that the measured speckle intensity pattern before and after deformation, can be used

to calculate the object’s full-field displacement vector from the reference and de-

formed configurations of a body. .

LITERATURE REVIEW 13 ElE

I lSubsequently the researchers at the University of South Carolina have improved the

technique [23]-[25],[52] and applied it to problems including rigid body mechanics

[22], displacement measurements in elastic bodies [26], fluid velocity measurements

[27], measurement of crack tip parameters [28], estimation of stress intensity factors

[29], plastic deformation observation [30], and measurement of strains in a paper

tensile specimen [31-32]. Recently they studied the effect of different interpolation

methods and other factors [33] on the accuracy of the technique.

The basic hardware utilized in their technique [26],[52] is similar to that shown in

Figure 6. lt consists of a white-light source, a video camera, a digitizer to convert the .

image into gray levels, a disc storage media to store this information, and a computer

to process the information into displacements and strains.

McNeill [52] has applied the technique to determine stress intensity factors in 2-D

cracked bodies, and used a hybrid numerical-experimental technique by combining

displacement data with a boundary element formulation to compute stresses. The 2-D

correlation technique was also extended to compute 3-D displacement using a non-

converging binocular system.

Sutton et. al. [23] have described an improved algorithm for correlation of reference

and deformed speckle images. This led to reduced computation time and the results

show that the algorithm can compute displacements larger than approximately 0.10

pixels. ln [24] they improved the algorithm by employing optimization theory [41] and

the work reported in reference [25]. The new correlation routine is 20 times fasterl

than the algorithm reported in [23].

I LITERATURE REVIEW 14

Digital correlation has also been investigated in Japan [42]-[44] for measurement of

deformation in inaccessible places such as inside a nuclear reactor. Dudderar et. al.‘ [45]-[46] in U.S. have also investigated this technique using a fiber optics white—light

source. Using a fiber optic bundle, however, requires that the minimum speckle size

must be at least three times the diameter of a single fiber in the bundle [46].

Fiber optics have been used both as a light source in harsh environments and to

transmit the speckle-field image from the remote test specimen back to an electronic

media for digitization and subsequent analysis [46].

To summarlze, surface motion studies using the speckle technique usually fall into

one of the two basic categories: methods that use coherent light to produce fringes

[1] and methods that utilize the digital correlation techniques [21,22]. The former ap-

proach has the advantage of simplicity. The disadvantage is that the few obtainable

fringes are often contamlnated with secondary speckle patterns from the coherentl

light used to process the specklegram. Also, the minimum resolvable deformation

_ is equal to the speckle size. ln contrast, the digital image processing method requires

a complex hardware system and sophisticated computer software. However, these

digital methods obviate the need for photographic work and are not limited to dis-

placements greater than the speckle size [45].

LITERATURE REVIEW 15

. _ ;

Consider an object that is illuminated by a light source. The light—intensity patterns

reflected from the undeformed and deformed object surfaces are shown in Figure 3.

Intensity patterns f(x,y)andf' (x’,y') in Figure 3 correspond to the reflected light

from the undeformed and deformed object configurations. The intensity patterns are

assumed to be in unique, one·to-one correspondence with the respective object

configurations. Therefore, using this basic assumption, one may measure the defor-

mations of small subsets of the image and thereby obtain deformations of small

subsets of the actual object surface [24].

3.1 Object Deformations °

The theory discussed in this section is presented' in detail in [40].

First consider the mathematical description of deformation. Every particle in the body

in an undeformed state has a set of coordinates. When the body deforms, every par-

‘ THEORY 16

I

inteneity Value

Defanned Image f'(x'.y')/‘ I 7/ IUndeformed Image I

" nenn-: H'W'x '

x.Area of Scanning

Figure 3. Gray-level representation of undeformed and deformed digitalspeckle images [26].

‘rHEORv 17

ticle takes a new position described by a new set of coordinates. For example, in

Figure 4, a particle P located originally at (x,y,z) is moved to P' with coordinates

(x’,y’,z') when the body moves and deforms. The displacement vector PP' has

components

x'—x, y’—y, z'—z.

lf the displacement is known for every particle in the body, a deformation can be de-

scribed by the displacement field. Let (x,y,z) refer to any particle in the original

configuration of the body and let (x', y', z') be the coordinates of that particle when

body is deformed. Then the deformation of the body is known if x', y', z' are known

functions of x, y, z ( Description of the subscripts is given in appendix A )

x,' = x,' (x, y, z) (3.1)

This is a transformation (mapping) from x, y,z to x', y', z'. In continuum mechanics .

we assume that deformation is continuous. We also assume that the transformation

is one·to-one; i.e., the functions in Eq. (3.1) are single—valued, continuous and have a

unique inverse for every point in the body. _

x, = x,(x', y’,z’) (3.2)

The displacement vector u is then defined by its components

u, = x/—x, (3.3)

lf a displacement vector is associated with every particle in the original position, we

may write ,

THEORY 18

1

z , z'

x'„y+dy',z+dz')

Q(x · ,y+dy,z+dz) u )xI·yI’zI

ds,P(¤•y•)

. y , yl ~

x , x'

Figure 4. Deformation of a body.

THEORY19

l

¤;(X- v- Z) = X/ (X, v- Z) — X; (3-4)

3.2 Strain

A rigid·body motion induces no stress. Thus, the displacements themselves are not

directly related to the stress. To relate deformation with stress we must consider the

stretching and distortion of the body. For this purpose, let us consider two neigh· ‘

boring points P and Q in the body. See Figure 4. lf they transformed to the points

P', Q' in the deformed configuration, the description of the change in distance be-

tween any two points of the body gives the deformation.

Let us consider an infinitesimal line element connecting the point P(x, y, z) to a

neighboring point Q(x —l- dx, y + dy, z + dz). The square of the length ds, is given by

dsä = dx2 + dy2 + dz2 · (3.5)

when P and Q are deformed to points P’(x’, y', z') and Q'(x’ +dx’, y' + dy', z' +

dz’),

respectively, the square of the length ds of the new element P'Q' is

dsz = dx'2+dy·2 +62*2 (3.6)

By Eq. (3.1) and (3.2) we have

I öx'„, öxm Idx m - öxi dx,, dx,„ - öX,i dx , (3.7)

Hence, on introducing the Kronecker delta, we may write .

‘n-usonv 20

ds = ÖH dx ,dx, = ÖH *5;;* dx, dxm (3.8)

The difference between the squares of the length elements may be written, after se-

veral changes in the symbols for dummy indices, as

öxlöx’ß

We define Lagrangian strain tensor

1 ö><’„„ öX'ß6H — 2 (öaß öxi öxj — ÖH) (3.10)

so that

2 2ds — dso = 26,, dx, dx, (3.11)

The strain tensor 6,, is symmetric; i.e., ·

EU =SjjAs

a consequence of Eq. (3.11) if ds*— dsä = 0 then 6,,= 0 and vice versa. But a de-

formation in which the length of every line element remains unchanged is a rigid-

body motion. Hence, the necessary and sufficient condition that a deformation of a

body be a rigid-body motion is that all components of the strain tensor 6,, be zero

throughout the body.

lf we introduce the displacement vector with components :

THEORY 21

ua =-j x'a—xa (oc=1,2,3) (3.13)

then

öx’a öua— E+Öa; (3.14)

and the strain tensor reduces to the form

_ 1 Öl!] öu, öua öuaEU- 2 öx, + öxj + öx, öxj (3°15)

We make very important assumptions here for digital image processing. First, we

assume that the out-of-plane displacement w does not affect the in-plane deforma-

tion or displacement of the characteristic intensity surfaces. This is typically true

when the object deformation is predominantly in plane; but it is not generaily true.

Secondly, we assume that the derivatives of out-of-plane displacement (i.e., )

are much less than terms like ( ) so that this effect may be excluded from Eq.

(3.15). We get three strains,

au 1 öu 2 öv 2”8""— öx+2|i(öx) +(öx)]’

_ öv 1 öu 2 _Qg_ 2j sw- (3.16)

.. J. E. Q2. £.q..<?y. aßS2"- 2[öy-*-öx+(öx öy+öx öy)i|

11-lEoRY · 22

3.3 Reconstruction of Digitally Recorded Intensity patterns

The first step in the analysis of object deformation is recording the two intensity pat-

terns by a digitizing hardware. The concept of gray-level representation of

undeformed and deformed images is shown in Figure 3. The intensity value at any '

sensor- known as a pixel (short for picture element, appendix B ) - usually ranges

from 0 to 255 (for a 8 bit digitizing board). A typlcal array of digitized intensity pattern

is shown in Figure 5. ‘

The object to be·tested is painted with a random array of black and white regions to

give the ’speckle appearance’. The advantage is each subset of the image is statis-

tically different than any other subset. Discrete values of intensity stored in the com-

puter are not the most advantageous for analysis because interpolation of these

° values is required between pixel locations for accurate subpixel displacement com-putations. Thus a surface fit through the data produces continuous function. One may

use several methods to fit such a surface including, bilinear, cubic, and polynomial

functions.

We should note here that the polynomial interpolation smooths the data much more

than the bilinear interpolation, thereby reducing the frequency content of the data set.

Therefore, the efficiency of the correlation routine is reduced, because the routine

operates better with a wide range of gray-level frequencies.

By using any of the interpolating methods, two intensity patterns (one for the

undeformed object and other for the deformed object) can be reconstructed. The

background information on the correlation and iterative procedure to obtain optimum

THEORY 23

correlation is shown in appendix B. The deformatlons which minlmize the difference

in intensity as given by Eq. (B.6) are defined as the local mapping of the actual object

surface [23].

The procedure for determining the minimum of a function of several variables is an

area of active research and in the future an improved scheme may become available

for minimization of this function.

THECJRY 25”

l

The goals of this research are to investigate the suitability of digital image processing

and computer vision for measuring deformation and strain on wood members, and to

use this method to measure the full-field deformation of two wood species stressed

in compression and bending.

4.1 General

The research work required hardware procurement, development of software, and

the study of fundamental modes of deformation. Data was gathered to evaluate the

digital image correlation method for measurement of deformation and strain in wood.

This work tests the hypothesis that there exists a subset within the body such that the

deformation in the subset may be expressed as a homogeneous deformation. lf sub-

sets are chosen sufficiently small and the various assumptions noted in the theory

section {are valid, then the method described is useful for both large and small def-

EXPERIMENTAL MATERIALS 26

ormations in wood. This hypothesis is supported by strain measurements done by

using this technique for problems in other fields [21-32,42-47].

A data acquisition system as shown in Figure 6 was used for all the experiments in

this project. The system included a video camera, a video monitor, a frame grabber

board, and an IBM PC-XT with a color monitor. The description of each piece of

hardware follows:

~4.2 Hardware ”

The video camera is a Sony CCD (Charge Couple Device) camera model XC-57. This

camera is essentially a transducer consisting of an array of 512x48O photo-sensors

which convert the light lntensity at each sensor into analog voltage that is propor-

tional to the light intensity. Each sensor location is called a pixel.

The video monitor is manufactured by Barco Industries, Belgium, model CD233 and

is used to display the image captured by the video camera. This video monitor oper-

ates at TV signals RS-170.

The frame grabber is manufactured by Matrox Inc., Canada, model PlP1024. lt has

four frame buffer memories and converts the camera signal from analog to digital

form for computer processing. This board can simultaneously accept signals from

three cameras. The frame grabber board can be programmed to continuously ac-

quire images or freeze a single image. A


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Figure 6. Schematic representatlon of the experimental set-up.

i EXPERIMENTAL MATERIALS 28

· l

The Vax/VMS 780 computer at the Center for Quantitative Studies, School of Forestry

and Wildlife Resources, Virginia Polytechnic Institute, was used for correiation anal-

ysis and displacement computation.

4.3 Software

The software for image grabbing, Vax emulation, file-transfer from PC to Vax and

digital correiation were written and made available for this project by Prof. McNeiII

[62]. The image grabbing software called MATROX6 [59] synchronizes the camera to

the video terminal for image display. The program also digitizes, stores, and retrieves

images. Several useful functions are available in the MATROX6 software including,

threshold (both on incoming signals and digitized signals), gain, and look-up table.

An important statistical property of any image is its gray-level frequency histogram.

MATROX6 can compute and display this histogram. All the functions available in this

software are described in appendix C.

The Vax emulation software allows an IBM PC to emulate and communicate directly

with a Vax/Vms computer. The file transfer—program called, FASTRAN uses Vax sys-

tem routines to transfer an image from an IBM PC (stored using MATROX6) to the Vax

in binary form.

The other program used in this project was the correiation routine. This routine

reads the gray-levels of the undeformed and deformed images stored in binary format

and correlates image subsets. The coefficients for bilinear interpolation are com-

puted from the gray-values of the deformed image. Next, the cross-correiation coeffi-


cient for the subset arrays of the undeformed and deformed images are computed.

The location of the undeformed image subset is based on user supplied coordinates.

The location of the deformed image subset is based on the user supplied estimated .

displacements. An area of $10 pixels around the undeformed image is searched for

a local maximum of the cross-correlation coefficient. This search continues lter-

atively and is terminated when the correlation coefficient reaches a predeflned toler-

ance. The details of the algorithm are in appendix B and a flow-chart is given in

Figure B.2 on page 96.

4.4 Speckle Patterns

One problem associated with using digital image processing to measure full-field

deformation is creating a random speckle pattern on the specimen surface. An ideal

speckle pattern will have have the following properties:

1. easy to apply on the specimen surface,

2. the speckle pattern deforms exactly with the specimen surface,

3. minimum speckle size greater than two pixels,

4. a wide gray-scale histogram,

The third attribute ensures that the detail of the speckle is not lost in digitization. The

fourth attribute ensures a large variation in gray-values from one image zone to an-

other. These two attributes strongly influence the correlation between two images.


lInthis study spray paint and adhesive-backed photographic film were the two meth-

F

ods used to create random speckle patterns on the specimen surfaces. Each method

has advantages and disadvantages for experimental stress analysis. The spray paint

technique has the advantage of creating a very thin coating on the surface which does

not influence the specimen surface deformation. Also different speckle density pat-

terns can be created to suit lighting conditions and magnification levels. The advan-

tage of the adhesive-backed film is its ease of application and its reproducibility. The

disadvantage of the photographic film is that it may not deform exactly with the

specimen surface.

Flat-white and flat-black fast drying spray paint were used to produce a black-dot

foreground on a white background. It was found during initial trials that this combi-

nation produces sharp, high contrast images. The gray-level histogram of a low

contrast image is a relatively narrow cluster of gray-values with other gray·Ievels

unoccupied. The histogram of high contrast images have multiple peaks spanning

most of the gray-level spectrum. The advantage of a high contrast image is that there

is large variation of gray—values from one image zone to another resulting in rapid

correlation convergence [60].

A typical spray paint pattern photographed. from the video terminal is shown in

Figure 7a. The spray paint pattern is created on a smoothly sanded (600 grit), clean

surface. The background is spray painted f|at—white. The black-dot foreground is

produced by using a spray-can with a slightly enlarged nozzle-hole. Researchers at

the University of South Carolina found that natural air currents create an acceptable

random speckle pattern. However, producing a very light coating with this procedure

is more art than science, and can be perfected only by practice.

EXPERIMENTAL MATERIALS r 31

I

The adhesive—backed photographic film (manufactured by Photech Imaging Systems,

Hackensack, New Jersey, type Photech GPF2 adhesive backed strip film) was made

from a photograph of a particularly well formed spray paint speckle pattern. This im-

age was enlarged to produce a pattern in the required scale. This technique has been

pioneered by the Professor McNeill’s research group at the University of South

Carolina. The preliminary experiments showed that the gray-level histogram for a

photographic film speckle pattern was wider gray scale and therefore contained a

better gray-level frequency content than the gray-level histogram obtained from most

spray paint patterns. Furthermore, the photographic film technique can produce en-

larged or compressed speckle patterns to suite the requirements of most exper-

iments. For example, a test with large displacements requires a film with large

patterns. On the other hand, a test with small displacements requires a film with

small patterns.

The film is applied to a smooth (sanded to 600 grit level), clean specimen surface.

Application involves cutting the film to the required size, removing the adhesive pro-

tective strip, and applying the film to the specimen surface with even pressure. Be-

fore an experiment the film surface is cleaned with lens cleaning tissue to remove

any grease or smudge marks.

For comparison, a theoretical random speckle pattern was produced using a uniform

pseudo-random generator subroutine in International Mathematical and Statistical

Library (IMSL) [61].

The patterns and the histograms obtained from spray paint, photographic film and

from the theoretical random pattern are shown in Figure 7 a,b, and c respectively.


l §l

4.5 Lighting Arrangement and Camera Mount

Lighting of the specimen surface plays an important role in producing sharp, high

contrast images, and also in producing images with a wide gray-level spectrum [63].

Uniform luminescence on the speckle pattern ensures that the gray-level character-

istics of the deformed and undeformed images are similar. This is important because

the light source does not translate with the specimen during deformation. Non-

uniform light may result in poor correlation between the undeformed and the de-

formed images because the change in light intensity is interpreted as a change in

gray-level. ln this study two types of light sources were used. First two incandescent

Photo-Ect Sylvania 500 Watts, 120V photographic bulbs were used; one was mounted

on each side of the camera (Figure 6). Second, a Sylvania 22 Watt fluorescent cir-

cular tube was arranged so that the camera pointed through the center _of the tube

as shown in Figure 8. The configuration produced more uniform light with less glare

than the incandescent bulbs.

ln most of the tests a standard photographic tripod was used for a camera mount. ·

The remaining tests used a Oriel Newport 36 series slide camera mount. This unit has

» a built-in micrometer for fine adjustment in two planes. Figure 8 shows the camera

and fluorescent light attached to this mount.1

The tests were conducted to establish accuracy (closeness to the true value),

preci-sion(closeness of a series of measurements to each other), and resolution of the

digital correlation method. The experimental procedure, results and discussion are

presented in the next chapter.


l

4.6 Specimens

Aluminum was used as the isotropic material in the study. The aluminum beams were

0.6 inch x 0.75 inch x 14 inch long. The aluminum compression block was of dimen-

sions 1 inch x 1 inch x 4 inch. The bending test used two wood species: Southern

yellow pine (Plnus spp.) and Yellow-poplar (Liriodendron tulipifera). The moisture

content of the YeIIow—poplar beam was 11.9% and specific specific gravity was 0.545.

Moisture content in Southern pine beam was 10.01% and its specific gravity was

0.543. The wood beams were 1 inch x 1 inch x 16 inch long. All the compression

wood samples were machined from southern pine boards. The parallel-to-the—grain

samples for static compression and creep compression tests were machined from a

4 feet long x 2 inch nominal thickness board. The measured moisture content of the

board was 10.07% and specific gravity was 0.544. The angle-to-the graln samples

were machined from a 6 feet long x 2 inch nominal thickness board. The compression

.sample with the knot was also machined from the second board. The moisture con- Ä Ä

tent and specific gravity of this board were 10.01% and 0.593 respectively. T

4.7 Testing Machines

All the experiments involving load application used a 22,000 pound capacity Material

Test System (MTS) servo-hydraulic testing machine. This machine has many advan-

tages for experimental testing of materials. For example, the machine can operate

with either load or displacement as the controlling variable. Load control causes the

hydraulic loading ram to move at a user defined load rate. Displacement control

ExPERiMEN‘rAL MATERIALS . 36

l

causes the loading ram to move at user defined stroke rate. With either control vari-

able the hydraulic ram can be held at a desired load or displacement. This capability

can be used for creep tests (load control) or relaxation tests (displacement control).

i ExPERlMEN1'AL MATERIALS — 37

l

5.0 EXPERIMENTAL PROCEDURES, RESULTS AND —

DISCUSSION

To determine the utility of the digital image processing method for displacement

measurement on wood, 5 series of tests were conducted: baseline tests, uniform

translation tests (rigid body motion), beam bending tests, static compression tests,

and creep compression tests. The baseline and uniform translation tests were con-

ducted to verify the hardware and software systems and to establish the minimum

sensitivity of the technique. The bending and compression tests were conducted on

both aluminum and wood specimens. Aluminum was included in this study because

the image processing method has been verified by other researchers on isotropic

materials and the material properties of aluminum are accurately known. Thus, the

displacement measurements can be compared to theoretical predictions for verifica-

tion of the hardware and software systems. After establishing the accuracy, sensitiv-

ity, and resolution of the system with the baseline tests and the translation tests,

experiments were conducted on wood specimens to measure displacements. As de-

scribed in chapter 4 several methods of applying the speckle pattern to_ wood sur-

EXPERIMENTAL PROCEDURES, RESULTS AND ¤lscUssl0N 38l

I

Ifaces were studied to determine ifthe methods developed for lsotropic materials [24]

_

are satisfactory for wood specimens.

5.1 Baseline Test y

Because digital image processing consists of a complex system of hardware, soft-

ware, and experimental skills the first series of tests were conducted to determine

the basic accuracy and precision of the method. The baseline test consisted of

producing two images of a speckle pattern on a stationary, unstressed specimen and

measuring the apparent displacements from the two images. ldeally, there will be no

measured displacements. In practice, however, random electrical noise in the image ·

signal can cause the gray-value at any pixel to vary from image to image. The details

of how an image is acquired by the image grabbing board can be found in reference

[57]. The random variation in the gray-values with respect to the mean gray-value is

called the signal to noise ratio. Baseline tests were conducted with both the speckle

techniques.

Table 1 contains the results of the baseline tests for both speckle techniques. Thetable shows the computedapparent displacements (in pixels) in the horizontaI(v) and

vertlcal(u) directions, and the cross-correlation coefficients at nine image zones de-fined by the x and y pixel coordinates. The results show that inherent system noise

for the spray paint speckle coating method is a maximum of 0.074 pixels for the ver-

tical direction and 0.276 pixels for the horizontal direction. For this image magnifica-

tion these displacements correspond to 2.84x10·° inch and 1.27x10·‘ inch in thevertical and horizontal direction respectively. The maximum cross-correlation coeffi-

EXPERIMENTAL PROCEDURES, RESULTS AND DISCUSSION 39

_ i

cient (computed from 1 — r) is 0.0001, indicating an excellent match between the two

images.

The inherent system noise for the photographic film technique is a maximum of 0.06

pixels in the vertical direction and 0.71 pixels in the horizontal direction. For this

magnlfication these displacements correspond to 2.30x10·‘ inch and 3.29x10·‘ inch

respectively. The maximum cross-correlation is 0.00015 indicating an excellent

agreement between the two images.

These results indicate the level of noise to be expected in the image analysis system,

and the minimum displacement measurable at this magnlfication level with these

speckle patterns. At higher magnlfication the system resolution may be improved. For

wood testing these minimum resolvable displacements are adequate.

Image averaging is a useful technique to reduce the effect of random noise [58]. A

composite image is produced from the numerical average of the grey level at each

. pixel obtained from a sequence of images. ln general, gray—Ievel frequency content

of the composite or averaged image is more reproducible and is more stable than

that of an unaveraged single image. To examine the usefulness of image averaging

for displacement measurement a second baseline test was conducted on another

spray painted speckle pattern surface. In this experiment, two composite images

were produced and compared. The composite images were made by adding gray

values at corresponding pixels from two images acquired in sequence and dividing

the sum at each pixel by number of images. The baseline test was repeated by av-

eraging over three and four images.


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Table 2 contains the results of the image averaging experiment. The table contains

the computed apparent horizontal and vertical displacements for an unaveraged im-

age, and composite images obtained from the average of two, three, and four images.

The results show that the maximum horizontal and vertical apparent displacements

for the unaveraged image are less than that of any averaged composite image. For

example, the maximum apparent displacements are 0.012 pixels, 0.034 pixels, 0.048

pixels, and 0.094 pixels for the unaveraged image, and composite images averaged

over two, three and four images, respectively. A similar trend is observed for the

apparent horizontal displacements. This finding shows that the image noise is not

additive [58] and cannot be reduced by image averaging. Furthermore, the numerical

treatment of composite images may produce truncation errors.°Therefore, unaver-

aged images were used for all subsequent tests in this study.

5.2 Uniform Translation Test

After completing the baseline tests, the noise effects, operating oharacteristics, and

fundamental precision of the measuring system were ascertained. The baseline test

represents measurement of infinitesimal motion caused by vibrations and noise in

the signal. The translation test was used to determine the accuracy obtainable from

digital image processing for finite motion.

The goal was to determine the resolution and accuracy obtainable from digital image

processing. This test was conducted by moving the specimen a known distance and

correlating the images taken before and after the translation.EXPERIMENTAL PRDCEDURES, RESULTS AND DIscUssl0N 42

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EXPERIMENTAL PROCEDURES, RESULTS AND DISCUSSION ‘ 43

l

The undeformed image was displayed on the video terminal and the coordinates and

the gray-level value of an individual point on the image were determined by the

l\/IATRÖXG software (see appendix C for details). Then the deformed image was dis-

played on the terminal and the new coordinates and gray-level value of the same in-

dividual point was recorded. The change in coordinates of the point between the two

images provides an estimate of the displacements (in pixels) and is used as a starting

point in the correlation routine. The displacements obtained from the correlation

method were then compared to the known translation to determine the accuracy.

A specimen coated with a speckle pattern was attached to a micrometer with a re-

solution of 0.001 cm. The translation test was conducted at various levels of magni-

_ fication so that the accuracy obtainable at each magnification could be determined.

The tests were conducted on wood specimens. Speckle patterns produced by bothi

the spray paint and the photographic film techniques were used on the specimens.

To obtain displacements in the horizontal and vertical directions the camera was

mounted first in the direction to measure horizontal displacements and then rotated

through 90° to measure vertical displacements. This arrangement simplified the tests

because it allowed the micrometer to remain stationary and thus minimized problems

with mounting the specimen to the micrometer. 1

Figure 9 shows the relationship between the known translation and the computeddisplacement for horizontal and vertical motion at three different magnification levels.

The figure shows excellent agreement between the actual and computed motion at

each magnification level. The maximum error is less than 3% and corresponds to thesmallest translation. Such a small displacement challenges the accuracy of themicrometer. Therefore, based on the results of the baseline test and translation test


1

the digital image correlation method seems capable of computing finite displace-

ments with excellent accuracy and low noise effects.

5.3 Bending Test

Bending tests were conducted to determine the measuring capability of the digital

imaging system because bending produces large displacements and displacement is —

the primary variable measured by the system.

All the experiments were conducted on simply supported beams with a single, center

point load. Cantilever beam bending tests were not used in this study because ofthe

difficulty of producing a truly fixed support condition due to the crushing of the wood

near the support.

A test frame with adjustable roller supports was used to produce a simply supported

boundary condition. By moving the supports it was possible to change the span for

various tests. Two sets of bending tests were conducted. First two aluminum beams

with cross-sections of 0.6 inch x 0.75 inch (width x depth) were tested. Then two wood

beams with 1 inch x 1 inch cross-section were tested. Two dial gages (accurate to

0.001 inch) were mounted under the beams, one at the center of the span, and the

other at a point away from the center. Figure 10 shows the testing arrangement.

EXPERIMENTAL PRDCEDURES, RESULTS AND DISCUSSION 45

0.140 = Vertical diaplacement

Magnification — 14-2.2 pixels/cm._ 0.12 -

E A = Vertical displacemcnt0I Magnification — 671.9 pixels/cm.

_g 0.10g e = Horizontal displacementg Magnification — 503.9 pixels/cm.8 0.08E

.9‘¤c.9 0.06EÜ AEU 0.04

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Micrometer movement — cm.

Figure 9. Results obtained from translation test at 3 magnification levels

1 EXPERIMENTAL PRDCEDURES, RESULTS AND DISCUSSION 46

5.3.1 Aluminum Beams

The speckle pattern on the aluminum beams was the adhesive backed photographic

film. The first beam was tested over a span of 12 inch. One thousand pound of load

was applied in steps of approximately 200 pound each. The camera was located par-

allel to the centerline of the span and focused on the center (neutral axis) of the

beam. The beam was destructively tested (beyond the yield point) and was not used

in subsequent tests. Images were acquired at each load step and compared to the

initial undeformed image to measure displacements.

Figure 11 shows the deflections measured with a dial gage and the deflections com-

puted from digital correlation at each load level. The maximum error between the

measurements is less than 2%.

The second aluminum beam was tested over 10 inch span to a load of approximately

550 pound in steps of approximately 100 pound each. The test was repeated three

times. The camera was mounted so that images were acquired at the span centerline

in the first test, 2.5 inch away from the centerline in the second test, and 1.25 inch

away from the centerline in the final test.

Figure 12 shows the deflections measured with a dial gage and the deflection com-

puted from the digital correlation method at each load level and at the three locations.

The figure shows excellent agreement between the measurements. The maximum

error is less than 3%.


1 L1° 11

0.20w

¤ = At the centerline

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g 0.15c(D gwE0:o.9¤..9T, 0.10 "’.9EEL. .O (9oE*5, 0. 05E .

0.000.00 0.05 0.10 0.15 0.20

Di¤l goge deflections — in.

Figure 11. Comparison of displacements of aluminum beam bending, span =12 inch: Photographic film speckle method used. Deflectionsmeasured at the centerline.


1 l

0. 06_

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Diol goge deflections — in.

Figure 12. Comparison of displacements of aluminum beam bending, span =10 inch: Photographic film speckle method. Deflections measuredat three locations.


i

5.3.2 Wood Beams

One yellow-poplar and one Southern pine beam of 1 inch x 1 inch cross section were

tested over a 14 inch span. The speckle pattern on the yellow-poplar beam was

produced with spray paint and photographic film was used on the Southern pine

beam. Load was applied in 100 pound increments to the center of the beam and im-

ages were recorded at each load level. Each test was stopped when a load of 500

pound was reached. Each beam was tested twice and images were recorded at the

center of the span and 3.5 inch from the span centerline.

The results for the yellow- poplar beam are in Figure 13. The figure compares the

deflections measured with a dial gage to the deflections computed from the digital

correlation method at each load level and at two locations on the beam. The maxi-

mum error between measurements is less than 6% and for most load levels the error

is approximately 5% for both locations on the beam.

Figure 14 shows the results of the Southern pine beam coated with the photographic

film speckle instead of spray paint as in the yellow-poplar beam in Figure 13. The

figure shows a larger error (8% maximum, 6.2% average) between the measured and

computed deflections at the span centerline than was observed with the yellow-

poplar beam. However, at the off-centerline location the error between computed and

measured deflections was less than that of the yellow-poplar beam. For the off-center

location the average error for the Southern pine beam was 3% and maximum error

was 6.5%.

ExPERnviENTAL PRocE¤uREs, RESULTS AND mscusslou 51

1

0.150©_ Q = At the centerline

.9I 0.125

L: A = 3.5 inch from centerline ©äE8 0.100

. g ©¤. A.9 .E 0.075 1.9E ¤·’935 0.050o A

Tg, inE5 0.025 ‘

0.0000.000 0.025 0.050 0.075 ” 0.100 0.125 0.150

Diol goge deflections — in.

Figure 13. Comparison of displacements for wood beam bending. Yellow-poplar, span = 14 inch: Spray paint speckle method. Deflectionsmeasured at two locations.


0.20

¤ = At the centerline

A = 3.5 inch from centerlineI_gg 0.15 ©5g A0:8E- ©E A·¤C 0.10.945 ©ELEQ A.

E co*5, 0.06A.

Q3

0.000.00 0.05 0.10 0.15 0.20

Diol goge deflections -1n.

Figure 14. Comparison of dispiacements for wood beam bending. Southern _yellow pine beam, span = 14 inch: Photographic film specklemethod used. Deflections measured at two locations.

EXPERIMENTAL PRocE¤uREs, RESULTS AND DISCUSSION 53

The results show that for wood specimens the spray paint and photographic film

speckle techniques give similar error magnitudes for displacements measured near

the point of load application. Although the error is consistently lower for the spray

paint pattern than for the film pattern at the centerline location a reverse trend is ob-

served for the off-centerline location. The aluminum beams showed no significant

difference in error magnitude between measurement locations. One reason for the

difference between the excellent performance of the film on the aluminum and in-

consistency of the film on the wood may be due to bonding characteristics of the

film’s adhesive. Apparently, the adhesive makes a better bond on the aluminum than

on the wood surface. Consequently, the film deformation lags behind the wood de-

formation. Also, the bond quality may not have been consistent at both locations

leading to different displacement error magnitudes at the two locations on the

Southern plne beam.

5.4 Compression Tests

After investigating the suitability of the digital correlation technique for measuring

deformation in beams, the method was applied to study its suitability for computing

compression deformations. A sub-objective was to compare the response of the two

types of speckle patterns on aluminum and wood specimens.

EXPERIMENTAL PROCEDURES, REsuLTs AND DISCUSSION 54

I

’ . · I

5.4.1 Aluminum Block

The aluminum compression specimen was 1 inch x 1 inch x 4 inch long. First, the

experiment was conducted with the photographic film speckle pattern. Then, the film

was removed and the specimen was coated with a spray painted pattern. Images

were recorded at t.he same location on the specimen for both tests. ln each test the

center of the image was 1 inch below the top of the specimen. Load was applied

in 2000 pound increments and images and strain were recorded at each load level.

Each test was stopped at 8000 pound.

Figure 15 compares the displacements in the load direction on the aluminum block

measured with both speckle techniques. —The displacements measured with the

spray paint method are consistently greater than those measured with the film pat-

tern. This result indicates thatideformation of the film pattern lags behind the defor- ~

mation of the aluminum block, since we assume apriori that the spray paint pattern

deforms perfectly with the block. However, the magnitude of the difference between

the two speckle methods is small and either method can be used to compute dis-

placements in the load direction.

Figure 16 compares the displacements in the transverse direction (due to Poisson’s

effect) measured with both speckle techniques. For comparison, at 8000 pound of

load the theoretical transverse displacement is 2.47x10“4 inch. The displacements

measured with the spray paint pattern was 5.62x10“4 inch and the displacement

measured with the film pattern was 19.72x10’4 inch. This indicates that for these

speckle patterns and this magnification the digital correlation method does not accu-

rately measure transverse deformations. One reason for the error may be due to

EXPERIMENTAL PROcEDUREs, RESULTS AND DiscUssl0N 55

9000

8000 A with photographic film A O

7000 0 with spray paint

6000 AouiEI 5000 ·

1:¤ .3 4000 A Q

3000

2000 Ao

· 1000

00 5 10 15 20 25 30 35 40

deflection — 1e—O4 inch

Figure 15. Loading direction displacements of the aluminum block in com-pression: Images were recorded at 1{E- inch from the top edgeof the specimen using both the speckle techniques.

EXPERIMENTAL PRocEDuREs, RESULTS AND DISCUSSION 56

lnoise effects because the magnitude of the transverse deflections is on the orderofone

pixel. The baseline tests showed that for this the system noise effect may be on .

the order of i 0.5 pixels. Therefore, when measuring very small displacements errors

are expected in the results. Another reason for the large error may be due to misa-

Iignment of the specimen plane with the image sensing plane in the camera. A slight

nonparallel arrangement would produce a parallax effect, and consequently, with very

small transverse displacements a large apparent displacement. The effect is not sig-

nificant in the load direction because of the relatively large magnitude of defor-

mations (3 to 4 pixels). Another reason for large difference between the theoretical

displacements and the digital correlation displacements is the edge effect (Saint

Venant’s effect) has not been accounted for when computing the theoretical dis-

placements. U

5.4.2 Wood Blocks: Parallel-to-grain

To compare the response of the two types of speckle patterns two straight grain

Southern yellow pine (Pinus Spp.) compression samples (1 inch x 1 inch x 4 inch

long ) were machined from one board. The first series of tests used the photographic

film speckle pattern and the second series used spray paint speckle pattern. For the

first test series specimen A was tested non-destructively, paralIel—to-grain with the

film speckle pattern located at 1.5 inch from the top and the bottom edges of the

sample. Specimen B was tested non-destructively, parallel—to-grain with the film

speckle pattern located at 1.5 inch from the top and bottom edges of the sample. After

completing the first test series the speckle film was removed from each specimen,

the sample surfaces were sanded, cleaned, and coated with a spray painted speckle


‘ I9000

8000 A 0

7000

6000 A 0uiEI 5000

‘¤03 4000 A O Awith photogrophic film

$000 O with sproy point

2000 A 0

1000

0 5 10 15 20 25


Figure 16. Transverse displacements of the aluminum block incompression: Images were recorded at 1% inch from the topedge of the specimen using both the speckle techniques.


l

pattern. The compression tests were repeated on the same samples and images

were recorded at the same locations on each specimen as in the first test series.

For both test series images were recorded at the following load levels: 300, 600, 1000,

1500, 2000, and 2500 pound. All the tests were stopped below the proportional limit

to avold damaglng the specimens. This test series produced 48 images: 2 images,

6 load levels, 2 speckle techniques, 2 locations, per specimen.

Figure 17 compares the deformations measured in the load direction with both

speckle methods at two locations on the specimen. The two speckle methods

produced similar deformation measurements at the top measurement location. How-

ever, at the bottom measurement location the dlsplacement of the film speckle pat-

terns consistently lagged behind those of the spray paint pattern. This indicates that

the photographic film adhesive may not have bonded properly to the wood surface.

Figure 18 shows the transverse deformations measured with both the speckle meth-

ods, at the top location on the specimen. Both methods produced similar dlsplace-

ments. For comparison, the theoretical transverse dlsplacement at 2200 pound is

6.32x10"'4 inch. The measured deformations by both speckle methods are an order

of magnitude greater than the theoretical value. Since the measurement location is

near the load point the theoretically computed dlsplacement may be erroneous due

to Iocalized stresses and Saint Venant’s effect. Therefore, no conclusion can be

drawn regarding the accuracy of the transverse deformation measurements. —


I

2500

1.5 inch from topAwith photographic film ¢* Oo with spray paint20001.5 inch from bottom Aa with photographic film0 with spray paint 4 O

ß 1500I A

E er ¤O.1 1000A .

Q O

500A‘ Ü

00 10 20 50 40 50

deflection —- 1e—O4 inch

Figure 17. Loading direction displacements of Southern pine block incompression-parallel-to-grain: Images recorded at 1.5 inch fromthe top and bottom edges of the specimen using both the speckletechniques.


. I

2500

4- 0 O

2000A

4- <> OU; 1.5 inch from topQ 1 500 Awith photographic film

I A o with spray paint

* O O 1.5 inch from bottom.1 owith spray paint

1 000A

4 with photographic film

4- O

500A

*0

0 10 20 30 40 50


Figure 18. Transverse direction displacements of Southern pine block incompression-paraIlel-to-grain: Images recorded at 1.5 inch from ~the top and bottom edges of the specimen using both the speckletechniques.


5.4.3 Wood Block: Variable grain angle

This test series was conducted to study the behavior of Southern pine (Pinus Spp.)

loaded in compression at various angles to grain, and the suitability of the digital

correlation method to measure displacements using both speckle techniques. Twotangentially edge-matched specimens for each of the following targeted grain angles

were machined from one board: 30°, 45°, 60°, 90° The exact grain angle of each sam-

ple was measured and recorded after machining. One sample of each grain angle

was coated with the film speckle pattern and its matched sample was coated with the

spray painted speckle pattern. images were recorded on the radial surface 1.5 inch

from the top of each sample at the load levels shown in Figure 19 to Figure 22.

Figure 19 to Figure 22 show the load—displacement relationship measured by both

speckle methods for the 30°,45°, 60°, and 90° to—the-grain specimens respectively.

‘Each figure shows the response in both the loading direction and the transverse di-

rection. The figures show that the compliance in the loading direction increases with

increasing grain angle. The figures also show that the compliance in the transverse

direction decreases with increasing grain angle.

For the 30° to the grain specimens (Figure 19) the displacements from the speckle

method were larger than those from the spray paint method for both the loading di-

rection and the transverse direction. The difference in the response between the two

speckle methods may not be solely due to the methods themselves but may be due

to the variation in the wood material since matched specimens were used for these

tests. A better experimental approach would utilize two cameras to simultaneously

record images from both speckle methods on a specimen.


Sl

For the 45° to the grain specimens (Figure 20) the displacements from the speckle

method were larger than those from the spray paint method for both the loading di-

rection and the transverse direction. A similar trend was observed for the 60°(Figure 21 ) and 90° (Figure 22) specimens.

Figure 23 shows the effect of grain angle on the load-displacement relationship in the

loading direction and Figure 24 shows the effect in the transverse direction meas-

ured by the spray paint speckle method.”

5.4.4 Wood Block with a Knot

Knots are natural growth characteristics that form when branches grow from the trunk

of a tree. A Southern pine specimen (1 inch x 1 inch x 4_ inch) with a tight knot (7%-

inch diameter) on the tangential plane was tested to determine if the digital corre-

lation method was suitable for measuring deformations at discontinuities in the ma-

terial. The specimen was coated with a spray painted speckle pattern and tested in

compression paraIlel—to-the—grain. Images were recorded at load steps of 200, 500,

1000, 1500 and 2000 pound.

Figure 25 shows the displacements in loading direction computed at four locations

around the knot at each load level. The figure illustrates that the stiffness ofthe clear

[


1

10003 750 O A

A1; 600 °¤ O AO 259 A n 6 .61—* ¤ A 6 $,,3,5 ,„L1'1‘l

00 25 50 75 100125

defl. x1e—O4 inch

3

1000‘ 750 O Ao A1; 600

¤ O A¤ A 16 6 .6*1-1 ”° 6 A 6 §„?„$,„L1'„?60

- 0 25 50 75defl. x1 e—O4 inch

b

Figure 19. Displacements of Southern pine block incompression—30°-to-grain: Images recorded at 1.5 inch from thetop edge of the specimen using both the speckle techniques -a)Loading direction b)Transverse direction

sxpznimaum. pnocsoumzs, Rssuus Ann mscussuou 64

I

750ui Q9

I 500 Q;ig OA-! 250 (A Aphoto. film

Osproy point

00 50 100 150 200

defi. x1e—O4 inch

a

750ui O A9I 500 o A"S o A

-3 250 A hoto filO A P „ FTIOsproy paint

00 25 50 75 100

defl. x1e—O4 inch

b

Figure 20. Displacements of Southern pine block incompression-45°-to-grain: Images recorded at 1.5 inch from thetop edge of the specimen using both the speckie techniques -a)Loading direction b)Transverse direction

EXPERIMENTAL PRocEDUREs, RESULTS AND DISCUSSION 65

625. 500 O A— 575TL 0 A

8 250 Aphoto.fiIm.11 25 O A O spray paint

00 50 100 150 200 .

def!. x1e—O4 inch

8

500 , AuiL f

575 A6 ”° 1 ht 1p o 0. ifm3 125 6 A

O spray paint0

0 25 50 75def!. x1e—O4 inch

b

Figure 21. Displacements of Southern pine block incompression—60°-to-grain: Images recorded at 1.5 Inch from thetop edge of the specimen using both the speckle techniques -a)LoadIng direction b)Transverse direction

ExPER11v1EnTA1. PROCEDURES, REsu1.‘rs AND DISCUSSION 66

1. 1

300U; Aphoto. film '

E AI ZÜÜ osproy point

OB A I3 100 AI <>

00 50 100 150 200

def!. x1e—O4 inch

a

300U; A photo. film£ A

I 200 o aproypoint

E ° A100 O.1 O A

00 5 10 15

defl. x1e—O4 inch‘

Figure 22. Displacements of Southern pine block incompression-90°-to-grain: Images recorded at 1.5 inch from the‘ top edge of the specimen using both the speckle techniques -a)Loading direction b)Transverse direction


I

1000

A6ta1'

600 66444** Ao¤xs5° 0

600 «¤tsa¤° AI

E <> <>3 400 A ·0 0

200 A O0 ” *

**

00 25 50 75 100 125 150 175 200


Figure 23. Effect of grain angle on compliance of wood in compression in theloading direction: Results shown for images recorded at 1.5 inchfrom the top edge of the specimen using spray paint speckle tech-nique.

axpsmmsnrm Pnocsounss, Rssuurs Ann oiscussnon 68

1000

A ¤t31·

600 6 ¤t44• Ao ¤ts6° O

(ig 600 6 (1t9Ü• A1

E <> <>3 400 A

o

200 OA2 A-

_ *0051015 20 25 30 35 40 45 50

deflection - 16-04 inch

Figure 24. Effect of grain angle on compiiance of wood in compression in thetransverse direction: Results shown for images recorded at 1.5inch from the top edge of the specimen using spray paint speckletechnique.

Ann mscussuou 69

l

wood is higher than that of the knot wood. Similar results are presented in reference

[64]. These results also illustrate the versatility ofthe technique in measuring full-field

deformation at the discontinuities.

5.5 Creep Tests

Creep is a phenomena of deformation with time under a constant load. Wood is a

rheological material and exhibits creep behavior particularly when exposed to cycllc

humidity conditions. At room temperatures aluminum does not exhibit marked creep

behavior. The objective of this test series was to determine if the two speckle tech- ·

niques are suitable for measuring the deformation over time on wood compression

samples.

Creep tests were conducted in compression parallel-to-grain on two pairs of matched

Southern pine specimens. Each pair of end·matched specimens were machined from

one 1 inch x 1 inch x 8 inch long board. One speclmen of each matched pair was

tested with the film speckle pattern and the other matched speclmen was tested with

the spray paint speckle pattern.

A constant load of 4000 pound ( approximately 50% of the ultimate load) was applied

to the first pair of matched specimens and images were recorded 1.5 inch from the

top ofthe specimens at the following times: O min., 0.5 min., 1 min., 2.5 min., 5 min.,

10 min., 15 min., 20 min., 30 min. and 40 min. A constant load of 6000 pound (ap-

proximately 75% of the ultimate strength) was applied to the second pair of matched

ExPERlMEn1‘Al. PRocEDuREs, REsuL.Ts AND DISCUSSION 70

· l

2000A center of knot0 inner boundary 0* *40 outer boundary

1 ÖÜÜ w clear wood

_ 6* Qß 1200 _I .

‘¤¤O.1 800 O D

400Q

00 5 10 15 20 25 30


Figure 25. Compression parallel-to-grain in loading direction in Southern pineblock with a knot: 5/16 inch diameter tight-knot located on thetangential surface at 2 inch from the top edge.


I I

specimens and images were recorded 1.5 inch from the top of the specimen at the

same time steps as the other load case.

Figure 26 to Figure 28 show the relative creep deformation versus time, measured

by both speckle methods for the specimens tested at 50% and 75% of the estimated

ultimate load respectively.

The response in the loading direction and the transverse direction are shown in Fig-

ure 26 and Figure 27 respectively for 50% load condition. The relative deflection for

both the loading direction and the transverse direction are remarkably similar. The

relative deflection measured by both speckle methods are also in close agreement

to each other. The film method measured consistently greater deflections in the

loading direction than did the spray paint speckle method, but the difference may be

due to the natural variation of wood material rather than the methods themselves.

For the specimens tested at 75% of the ultimate load Figure 28 and Figure 29 show

the response for the loading direction and transverse direction respectively. The

relative deflection for the loading direction and the transverse direction are of similar

order. The creep observed in the specimen coated with the spray paint speckle pat-

tern was twice that in the specimen coated with the photographic film pattern. The

relative deflections computed from digital correlation also show the similar trend for

the two speckle methods.

EXPERIMENTAL PROCEDURES, REsULTs AND Discussiou 72

1

109

AA

g 8nvi 6 OE 6 A O

4. A

O A with photographie filmO 0 with sproy point

G).2 O§ 2 Azu*— O1

° .0

0 5 10 15 20 25 30 35 40 45 50

Time — min.

Figure 26. Creep in a Southern pine block in the loading direction - com-pression parallel-to-grain at 50% of the estimated ultimate load:images recorded at 1.5 inch from the top edge ofthe specimen usingboth the speckle techniques.


_ 2

8A with photographic film

7 A_: o with spray paintE 6 og 6 A o

· é9 6 6[ A

E 4 6 ¤-4-JU2 o0)

G.) O.2§ 2gg Ao

1 O

0° 0 5 10 15 20 25 30 35 40 45 50

Time — min.

Figure 27. Creep in a Southern pine block in the transverse direction - com-pression parallel-to-grain at 50% of the estimated ultimate load:Images recorded at 1.5 inch from the top edge ofthe specimen usingboth the speckle techniques.

Expsmmaum. mocsounss, Rssums Am: mscussicm 74

· I

50O

L 25 °0EE O(L 20T" O

| A15 o

02 A“<$ A'Ugp io O A photographie film~ .2 A“6 .Q A o spray paintS.

5 O A . ’q\A

00 5 10 15 20 25 30 55 40 45 50

Time — min.

Figure 28. Creep in a Southern pine block in the loading direction - com- 'pression parallel-to-grain at 75% of the estimated ultimate load:Images recorded at 1.5 inch from the top edge of the specimen usingboth the speckle techniques.


l5 0

0.CE 4 O<r?Q) O

n 3 _E ¤*6 A A„ij A.g 2 0 A A0).2*6 A A photogrcphic filmEA. O

1 A o aprcy point

gl

A

00 5 10 15 20 25 30 35 40 45 50

Time — min.

Figure 29. Creep in a Southern pine block in the transverse direction - com-pression parallel-to-grain at 75% of the estimated ultimate load:Images recorded at 1.5 inch from the top edge ofthe specimen usingboth the speckle techniques.

[

Exi>ERi~iEmAi. Pnocsoumss, Rssums Ann oiscussiou 76

l

6.0 SUMMARY, CONCLUSIONS AND

6.1 Summary

A digital image processing system was used to measure the full—fieId deformation on

aluminum and wood specimens loaded in compression and bending. The measure-

ment technique consists of creating a random speckle pattern on the specimen sur-

face, recording images before deformation and after deformation, and computing the

relative displacements of small image subsets. Two methods for producing speckle

patterns on the specimens were studied: spray paint and adhesive—backed photo-

graphic film.

To evaluate the influence of signal noise on the measurement system baseline tests

were conducted by computing the apparent displacements of two images recorded

from the same location on an unstressed Specimen. The results showed that for the

SUMMARY, coNcLUs¤oNS AND REcoMMEN¤ATloNS FOR FUTURE RESEARCH 77

}magnification and speckle patterns tested displacement measurements smaller than

3.29x10'4 inch (8.35x10'3 cm.) may be unreliable due to signal noise.

Uniform translation tests were conducted to evaluate the capability of the system for

measuring finite motion. The system was verlfied with a minimum translation of

5.9x10"3 inch ( 0.015 cm.). Finer resolution may be achieved with higher magnifica-

tion and micrometers with higher accuracy.

Bending tests were conducted on aluminum and wood specimens. Displacements

obtained from the digital method were compared with deflections measured with a

dial gage. Excellent results were obtained for the aluminum beams coated with pho-

tographic film speckle patterns (less than 3% error). However, the results for the

wood specimens had a higher magnitude of error. The deflections measured by the

spray paint method were approximately 6% higher than the dial gage deflections. The

deflections measured by photographic film speckle method were 8% greater than the

deflections measured with the dial gages.

To determine if the speckle method influences the results aluminum and wood com-

pression were tested with both speckle methods. On aluminum, the displacements

measured by the photographic film method were consistently less than those meas-

ured by the spray paint method for both load the direction (12% maximum difference)

and the transverse direction (70% maximum difference).

On wood, the displacements measured in the loading direction by the photographic

speckle method were approximately 15% greater than those measured by the spray

paint speckle method. ln the transverse direction the displacements measure by theSUMMARV, CoNCl.USloNS AND RECDMMENDATIDNS FOR FUTURE RESEARCH 78

i

photographic film speckle method were approximately 70% lower than those meas-

ured with the spray paint speckle method.

Compression samples loaded at four grain angles were also tested with both speckle

methods. The results show good agreement between displacement measurement by

both speckle methods for the displacements in the loading direction. For the trans-

verse to-load direction large differences _existed between the displacements meas-

ured by the two speckle methods. However, since the compression tests were

conducted on matched specimens, the material property variation from specimen to

specimen may contribute to the error. The edge effects will also contribute to the er-

ror.

A southern pine sample with a knot was tested with the spray paint speckle tech-

nique. The results show that the clear wood is stiffer than the knot wood. These re-

sults agree with the results in the literature [64].

l\/latched wood samples were tested for creep in compression parallel-to—grain to

evaluate the system’s suitability for long-term measurements. The results indicate

that both speckle methods produced similar results for both the load direction and the

transverse direction.

Since the spray paint speckle method was assumed apriori to produce reliable dis-

placements, the computed displacements from the compression tests were not veri-

fied against displacements from an independent test. This is a limitation of this work.

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE RESEARCH 79

l

6.2 Conclusions

This work supports following conclusions:

1. The digital correlation method is capable of accurately measuring rigid body dis-

placements as shown by the translation and bending tests.

2. The digital correlation method did not accurately measure the transverse dis-

placements of compression samples; probably due to several reasons including

misalignment effects, edge effects, and the small magnitudes of the displace-

ments.

3. The digital correlation method is capable of measuring displacements in the

loading direction from static and creep compression tests.

4. On wood, the adhesive film speckle method produces inconsistent results in

bending, static compression and creep compression. The fiIm’s response gener- Lally lags behind the specimen surface response; probably due to an incompat-

ibility between the wood surface and the adhesive. But, on the aluminum

compression samples the displacements measured with the film lagged behind ·

those measured by the spray paint speckle method. Therefore, the adhesive

backed film system may not perform adequately in compression even on alumi-

num specimens.

5. The film and the spray paint speckle pattern on same the specimens produced

different results. Therefore the film system needs to be modified to improve its

performance.·

l

I

SUMMARY, coNci.UsloNs AND RECOMMENDATIONS FOR FUTURE RESEARCH 80

I· I

6.3 Recommendation for future work

FulI—field strains were not computed in this study. A program to compute full-field

strain would help in understanding the behavior of wood. The full-field strain meas-

urement can be used to study the discontinuities arising because of natural variation

in wood material, for example, the discontinuity between the early—wood and late-

wood zones. Computation of full-field displacements on wood specimens in tension

and shear will verify the image processing system for different loading conditions and

help in understanding the response of the two speckle methods.

A method of superimposing the wood image on the full—field displacements computed

from the digital correlation method would be useful for studying the effect of anatomy

on mechanical behavior of wood.

A study of different speckling techniques to produce random patterns on the speci-

men surface is also recommended. For example, photocopy powder when hot

pressed can create a semi·permanent speckle pattern. Other combinations of film

material and adhesive may also produce speckle patterns with better response on

wood.

Another area of study recommended here is the development of a full-field displace-

ment computation system which does not rely on a random pattern. This system will

widen the scope of digital image processing and allow the method to be used on

structures where speckle patterns cannot be applied. Research is already being car-

ried out to compute displacements and strains for television images [51] and this

principle can be used to develop the recommended system.

SUMMARY, CDNCLUSIDNS AND RECDMMENDATIDNS FOR FUTURE RESEARCH 81

i•

[1] Erf, Robert K. (ed.) "Speckle MetroIogy" Academic Press, New York, 1978,pp.331

[2] Yu, Francis T. S. (ed.) "White Light Optical Signal Processing " John Wiley &Sons, Inc., New York, 1985, pp.116

[3] Sprague, R. A. "Surface roughness measurement using white light speckle,"Applied Optics vol.11, no.12, Dec. 1972, pp. 2811-2814

[4] Parry, G. "Some Effects of Surface Roughness on the Appearance of Speckle ·° in Polychromatic Light," Optical Communications, vol.12, no.1, sept.1974, pp.75-77

[5] Parry, G. "The Scattering of Polychromatic Light from Rough Surfaces : FirstOrder Statistics," Optical Quantum Electron., vol.7, no. 4, 1975, pp. 311-319

[6] Hariharan, P. "Speck|e Patterns: A Historical Retrospect," Optica Acta, vol.19,no. 8, 1972, pp. 791-799

[7] McKechnie, T. S., "lmage-Plane Speckle in Partially Coherent Il|umination,"Optical Quantum Electron., vol.8, no.7, 1976, pp. 61-

[8] Fujii, H., and Asakura, T., "StatisticaI Properties of Image Speckle Patterns inPartially Coherent Light," Nouv. Rev. Opt., vo|.6, no.3, 1975, pp. 5-19

[9] Boone, P. NI., and De Backer, L. C., "Speckle Methods using Photography andReconstruction in lncoherent Light," Optik, vol.44, no.3, 1976, pp. 343-355

[10] Burch, J. NI., and Forno, C., "A High Sensitivity Moiré Grid Technique forStudying Deformation in Large Objects," Opt. Engg., vo|.14, no.2, 1975, pp.178-185

[11] Chiang F. P., and Asundi A., "White Light Speckle Method of Experimental StrainAnalysis," App/. Opt., vol.18, no.4, 1979, pp. 409-411

[12] Burch, J. NI., and Forno, C., "High Resolution Moire Photography," Opt. Engg.,vol.21, no.4, Jul-Aug 1982, pp. 602-614

REFERENCES 82

III

[13] Chiang, F. P., and Asundi, A., "Theory and Applications of White Light SpeckleMethod for Strain Analysis," Opt. Engg., vol.21, no.4, Jul-Aug 1982, pp. 670-680

[14] Asundi, A., and Chiang, F.P. "Separation of 3-D Displacement Components inthe White Light Speckle Method," Optics and Laser Tech., vol 14, 1982 pp. 11-45

[15] Asundi A., "White Light Speckle Method for Strain AnaIysis," Ph.D. Dissertationin Mech. Eng. State University of New York, Stonybrook, Dec., 1981, 145 pp.

[16] Krishna Mohan, N., Joenathan, C., Sharma, D. K., and Sirohi, R. S. "Applicationsof Multi-Aperture White Light Speckle Photography," Optik, vol.79, no.1, Apr.1987, PD. 7-11

[17] Burch, J. M., and Forno, C. "Optical Methods for Measuring Strain," Stressesand Strains in Textile Structures, Shirley Inst., S10c, 1973, pp.6

[18] Benckert, L., Jonsson, M., and Molin, N-E “Measuring True In-Plane Displace-ment of a Surface by Stereoscopic White Light Speckle Photography," Opt.Engg., vol.26, no.2, Feb. 1987, pp. 167-169

[19] Jonsson, M., and Benckert, L. "Measurement of Residual Deformations in ButtWelded Plates by Use of White Light Speckle Technique," J. of Strain Analysis,vol.21, no.4, 1986, pp. 243-246

[20] Lahart, M. J. "Optical Area Correlation with Magnification and Rotation," J. ofthe Opt. Soc. of America, v0|.60, no.3, Mar. 1970, pp. 319-325

[21] Peters, W. H., and Ranson, W. F. "DigitaI Imaging Techniques in ExperimentalStress AnaIysis," Opt. Engg., vol.21, no.3, May-Jun. 1982, pp. 427-431

[22] Peters, W. H., Ranson, W. F., Sutton, M. A., Chu, T. C., and Anderson, J. "Ap-plications of Digital Correlation Methods to Rigid Body Mechanics," Opt. Engg.,vol.22, no.6, Nov.—Dec. 1983, pp. 738-742

[23] Sutton, M. A., Wolters, W. J., Peters, W. H., Ranson, W. F., and McNeiI|, S. R."Determination of Displacements using an lmproved Digital CorrelationMethod," Image & Vision Computing, vol.1, no.3, 1983, pp. 133-139

[24] Sutton, M. A., Cheng, Mingqi, Peters, W. H., Chao, Y. J., and McNeilI, S. R."Application of an Optimized Digital Correlation Method to Planar deformationAnaIysis," Image & Vision Computing, vol.4, no.3, Aug. 1986, pp. 143-150

[25] Tian, Qi, and Huhns M. N. "A Fast Hill-Climbing Algorithm for Subpixel Regis-tration," International Conference on Pattern Recognition, vol.1, 1984, pp. 13-15

[26] Chu, T.C., Ranson, W.F., Sutton, M.A., and Peters, W.H. "Applications ofDigital-Image-Correlation Techniques to Experimental Mechanics," Exper-imental Mechanics, Sept. 1985, pp. 232-244 ·

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[27] He, Z.H., Sutton, M.A., Ranson, W.F., and Peters, W.H. "Two Dimensional Fluid-Velocity Measurements by Use of Digital-Speckle Correlation Techniques," Ex-perimental Mechanics, Jun. 1984, pp. 117-121

[28] Peters, W. H., Ranson, W. F., Kalthoff, J. F., and Winkler, S. R. "A Study of Dy-namic Near-Crack-Tip Parameters by Digital Image Analysis," Journal DePhysique, Colloque C5, suppl, au n.8, Tome 46, aut 1985, pp. 631-638

[29] McNeiII, S. R., Peters, W. H., and Sutton, M. A. "Estimation of Stress IntensityFactor by Digital Image Correlation," Engineering Fracture Mechanics, vol.28,no.1, 1987, pp. 101-112

[30] Lee, C., Peters, W. H., Chao, Y. J., and Sutton, M. A. "lmproved Digital ImageProcessing Technique to lnvestigate Plastic Zone Formation in Steel," Imageand Vision Computing, vol.4, no.4, Nov. 1986, pp. 203~207

[31] Sutton, M. A., and Chao, Yuh J. "Measurement of Strains in a Paper TensileSpecimen using Computer Vision and Digital Image Correlation, Part 1: Dataacquisition and Image Analysis System," Tappi Journal, vol.71, no.3, Mar. 1988,pp. 173-175

[32] Chao, Yuh J., and Sutton, NI. A. "Measurement of Strains in a Paper TensileSpecimen using Computer Vision and Digital Image Correlation, Part 2: Tensilespecimen test," Tappi Journal, vol.71, no.4, Apr. 1988, pp. 153-156

[33] Sutton, M.A., McNeill, S.R., Peters, W.H., Jang, J., Balai, M., and Chao, Y.J."Error Estimate for Sub-Pixel Measurement of Object Deformations fromQuantized Image Intensity Data," Society for Photo Instrumentation Engineers,voI.814, Photomechanics and Speckle Metrology, 1987 pp. 774-784

[34] Bailey, H.H., Blackwell, F.W., Lowery, C.L. and Ratkovic J.A. "lmage Corre-lation: Part l Simulation and Analysis," Rand report R—2057l1-PR, Nov. 1976

[35] Wesley, H.W. "lmage Correlation: Part ll Theoretical Basis," Rand reportR-2057/2-PR, Nov. 1976

[36] Hoadley, R.B., "Strain Analysis in Wood by Means of Moiré Patterns," ForestProduct Journal, vol.16, no.5, May 1968, pp. 48-50

[37] Wilkinson, T.L., and Rowlands, R.E. · "Analysis of Mechanical Joints in Wood,"Experimental Mechanics, vol.21, no.11, Nov. 1981, pp. 408-414

[38] Rowlands, R.E., Rahman, M.U., Wilkinson, T.L., and Chiang, Y.I. "Single- andMultiple- Bolted Joints in Orthotropic Materials," Composites, vol.13, no.3, Jul.1982, PP, 273-279

[39] Matthys, D.R., Dudderar, T.D., Gilbert, J.A., Taher, M.A. and Johnson, H.S."Stress Analysis Combining Speckle Metrology with Finite Element Model|ing,"Society for Photo Instrumentation Engineers, vol.556, lnt. Conf. on Speckle, 1985

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[40] Fung, Y.C. "A First Course in Continuum Mechanics" Prentice—Hall, lnc.,Englewood Cliffs, N.J., 1977, 340 pp.

[41] Everitt, B.S. "lntroduction to Optimization Methods and their Applications inStatistics" Chapman and Hall, London, New York, 1987, 88 pp.

[42] Yagawa, G., and Matsuura, S. "Development of Point Recognition Picture Proc-essing for Deformation and Strain Measurement," J. of Fac Eng, Univ Tokyo serA, vo.22, 1984, pp. 40-41

[43] Soneda, M., Yoshimura "Measurement of the Dynamic Strain Field Near a Cracktip using Computer Picture Processing," Nippon Kikai Gakkai Ranbunshu Atten,vol.52, no.476, Apr. 1986, pp. 1105-1109

[44] Yagawa, G., Miyoshi, A., Yoshioka, A., and Soneda, N. "Deve|opment of a StrainMeasurement Method for Non-Plane Specimens by Means of Computer PictureProcessing," Nippon Kikai Gakkai Ranbunshu Atten, vol.53, no.491, Jul. 1987, pp.1408-1411

[45] Dudderar, T.D., and Gilbert, J. A., "Fiber Optic Measurement of the DeformationField on a Remote Surface Using Numerically Processed White-Light Speckle,"Applied Optics, vol.21, 1982, pp. 3520-3527

[46] Dudderar, T.D., Gilbert, J.A., Beohnlein, A.J., Schlutz, l\/l.E., "Application of FiberOptics to Speckle Metrology - A Feasibility Study," Experimental Mechanics,vol.23, no.3, 1983 pp. 289-297

[47] l\/letwalli, S.M., Ragab, A.R., Kamel, A.H., and Abdul Saheb, A. "Determinationof Plastic Stress-Strain Behavior by Digital-Image-Processing Tecniques," Ex-perimental Mechanics, vol.27, no.4, Dec. 1987, pp. 414-422

[48] Perry, C.C. "The Resistance Strain Gage Revisited," Experimental Mechanics,vol.24, no.4, Dec. 1984, pp. 286-299

[49] Garland, E. and Ehrich, R.W. "A GIPSY primer" Spatial Data Analysis Laboratory,Virginia Polytechnique Institute and State University, Blacksburg, Oct. 1986

[50] Rosenfeld, A. and Kak, A.C. "Digita| Picture Processing" Academic Press, NewYork, 1976, pp. 457

[51] Nagel, H-H. "Displacement Vectors Derived from Second Order lntensity Vari-ations in Image Sequences," Computer Vision, Graphics, and image Processing,vol.21, 1983, DD. 85-117

[52] McNeiII, S.R. "Use of Digital Correlation for Determining Fracture Parameters,Stresses, and 3-D Displacements," Ph. D. Dissertation, Mechanical EngineeringDept., Univ. of South Carolina, 1986, 119 pp.

[53] Vest, C.lVI. "Holographic lnterferometry" John Wiley & Sons, New York, 1979,chapter 3REFERENCES 85

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[54] Ballard, D., and Bron, C. "Computer Vision" Prentice-Hal/, Eng/ewood C/iffs, N.J.,1982 pp. 39-42

[55] Heywood, R.B. "PhotoeIasticity for Designers" Pergamon Press, 1969, 435 pp.

[56] ASTM Designation: D143-83 "Standard Methods of Testing Small Clear Speci-mens of Timber" Philadelphia, 1988

[57] Baxter, G.A. "Digital Image processing · A Practical Primer" Prentice HallEng/ewood C/iffs, N.J., 1984 182 pp.

[58] Gonzalez, R.C., and Wintz, P. "Digital Image processing" Addison Wesley,Reading, Mass., 1987, pp. 151-154

[59] Mcl§leill, S.R. "MATROX6 - Digital Image Processing software" Copyright 1987,Dept. Of Mechanical Engineering, University of South Carolina, Columbia, 1987

[60] Dvornychenko, S., "Bounds on (Deterministic) Correlation Functions with Ap-plication to Registration" IEEE transactions on Pattern Analysis and MachineIntelligence, v0l.PA|\/ll-5, no.2, l\/lar., 1983, pp. 206-213

[61] IMSL "User’s manual, StatlLibrary, Fortran Subroutines for StatisticalAnalysis" International Mathematical and Statistical Library Raleigh, N.C., 1987,chapter 18

[62] McNeil|, S. R. "FAST, FASTRAN Vax emulation and communicatiion routines "Copyright S.R. McNeiI/, 1989 Dept. of Mechanical Engineering, University ofSouth Carolina, Columbia

[63] Purll, D.J. "Chapter 5 - Optics for Image Sensors" in Automated Visula In-spection ed. by Batchelor, B.G., Hill, D.A., Hodson, D.C. IFS Publications Ltd.,‘ U.K. pp.73—81

[64] Bodig, J., and Jayne, B.A. "Mechanics of Wood and Wood Composites" VanNostrand Reinhold, New York, 712 pp.

[65] Haygreen, J.G., and Bowyer, J.L. "Forest Products and Wood Science An Intro-duction " Iowa State University Press, Ames , 1989, 500 pp.

ß REFERENCES 86

_ 2i

Appendix A. DESCRIPTION OF STRAIN TENSOR

FORMATION

A.1 Subscripts

Ali the subscripts used in section 3 (i,j, /, m, oc etc.) vary from 1 to 3. The sub-

scripts in 1,2,3 directions stand for x,y,z or x', y', z' directions respectively. That

TTIQHUS,

ua (oc = 1, 2, 3) stands for u, v, w respectively

Appandax A. osscmpnou or STRAIN ranson •=oRiviA7¤o~ 87

iI

‘ ·

IA.2 Differential Length

Hence Eq. (3.7) using Eq. (3.4) can be expanded in two dimension as:

, _ öx’ 0x'dx - ——öX dx-)-Ty dy, dx’=

lj—dx—I-dx—I-ädyöx 0ydy’=dx

öy, - Q Qdy —

öxdx—I—dy—I—

öy dy

Appendix A. DESCRIPTION OF STRAIN TENSOR FORMATION 88

l

Appendix B. NUMERICAL PROCEDURE FOR

DEFORMATION ANALYSIS USING DIGITAL

IMAGE CORRELATION

The digitization of a video image gives an array of numbers, each number re-

presenting the average light intensity over small areas of the image sensing

plane. The numbers representing the average light intensity are referred to as

gray levels and the areas their average value are taken over referred to as pixel.

Pixels are typically arranged in a grid like pattern [52].

Description given in this appendix is presented in detail in [21,26].

Appendix B. NUMERICAL PROCEDURE FOR DEFORMATION ANALYSIS USING DIGITAL IMAGEGORRELATION 89

II

B.1 Background

Consider a small subset of the undeformed object centered at P before defor-

mation, as shown in Figure B.1. After deformation, the subset center moves to

a new point P' and the subset deforms. lf we use the deformation assumption

made earlier, we can write the intensity values at positions P and P' as:

I f(P) = f(><„y) (B 1)F (P') = Fix + u(P), y + v(P)] ‘ °

Similarly, for a point Q at position (x + dx, y aj dy) on the undeformed object,

and O' being corresponding point on the deformed object, we can write the in-

tensity values at positions Q and Q' by:

f(O) = f(x + d><„ y + dy) (B 2)_ f’(Q’) = f'[x + dx —I— u(Q), y -I— dy + v(Q)] '

Finally, if we assume that the intensity pattern deforms but does not alter its Io-

cal value due to deformation we have:

f(P) = f’[x + u(P), y + v(P)] B 3f(Q) = f'[x + dx —+- u(Q), y + dy -I— v(Q)] ( ' )

Appendix B. NUMERICAL PRDGEDURE FDR DEFORMATION ANALvsIs USING DIGITAL IMAGEcoRRELATIoN so

I

II

fix.!)f'(¤'.y')

Deformed Subimage

t'<P'>Undeformed Image.4 (Alf

1—lI ’ "”

x , x' Area of Scanning

Figure B.1. Local Distortion of a Subset Image [26].

Figure B.2 shows a small subset on the undeformed object surface centered at

P, together with its deformed shape centered at P'. lf we assume that the sub-

set is sufficiently small that straight lines remain straight after deformation, then

we can use Eqs. (A.1) to describe the position of point Q' as:

Appendax B. NUMERICAL PRocE¤uRE FOR DEFORMATION AI~IALYsIs USING DIGITAL IMAGECORRELATION 91

I

I

Uudeformed aubimage Area of Iaeanuing +V0 YP fe Tr

I II !•!'I Ar , „ AY"

· I I II

-III--Il--III--.-IIIIIIIIIIIIIIIIIIII--IIIIIIIIIIIIlllllllllllllllll_ ___ IIIIIIIIIIIIIIIII’Ax III-EQIIIIIIIIIIIzi ‘— IEIIISIIIIIIIIIIIIIIIIlEF===§IIIx'; ··—· =l=l=l=Il=CIIlIII ¤¤bi¤¤¤z¤jf __ IIIIIIIIIIIIIIII Pixel‘° IIIIIIII!§ll-!IIII ¤¤¤¤¤¤¤lllllllllllnulll g¤;äpu¤¤

III.----------- "-I--III-III---.

+ x,x'

Figure B.2. Deformation of a Subimage in a Sampling Grid [26].

Appendax B. NUMERIGAL PROCEDURE FDR DEFDRMATIDN ANALYSIS USING DIGITAL IMAGECORRELATION 92

. E

(XII, yII) (XI + dxl, yl+=[x -4- u(P) -4- dx’, y + v(P) -4- dy']

· öu öu- [x + u(P) + ÖX dx -4- öy dy + dx, (B.4)

öv övy+v(P)+ öx dx-l- ay dy+dy]

Using Eq. (B.4), Eq. (B.3) can be re-written as:

, öu öuf'(Q) = f[x -4- u(P) -4- E- (P)dx -4-E

(P)dy + dx,

+ v(P) d (P) + d ](BIS)

y öx öy y y

Thus, if we know the displacement of the center point P of a subset and if we

. . . öu öu . .obtain the derivative terms 797(P), —5(P), then the position of any nearby

_ point Q' is determined. Conversely, if we assume values for

öu öu öv öv .u(P), v(P), öx (P), öy (P), öx (P), and öy (P), then we can compute esti-

mates for the positions of the the point P' and all points Q' that are within the

small subset surrounding P' This last statement is the foundation for the nu-

merloal computation of local deformation.

Appendix B. NUMERIGAL PROGEDURE FOR DEFORMATION ANALYsIs USING DIGITAL IMAGEGORRELATION 93

l

B.2 Iterative Method

To obtain accurate values for the six variables of interest in any subset, we must

compare subsets of intensity pattern. The method for comparing two subsets is

given by cross-correlation coefficient, C, [23-26,34-35]

öu öu öv öv[ - C(U’V’öx’öy’öx’öy)

= fAMf(><„y)¢”(><+ é,v+v)<//I (B-6)f r 2dA f r 26 2

where AM is subset in undeformed image .

AM' is subset in deformed image '

‘öu öuand §—u—l—ÖX Ax+ öy Ay

öv öv‘

ry—v+ ax Ax-l- öy Ay

The values of u, v, Qi, E-, -@2-, and gg- which maximize C are theöx öy öx 0y

local deformation values for a subset. As a first approximation only (u, v) are

assumed to vary; while rest of the variables are set to zero. This gives

(u1, v1), which are first approximation of translation of point P. Next, (u, v) are

held at (u1, v1) and %,—g—;§ are chosen to vary while jä-,%(‘L are zero.

[

Appendix B. NUMERICAL PROCEDURE FOR DEFORMATION ANALYSIS USING DIGITAL IMAGEcoRmsi.AT¤ou 94

EThis gives a first approximation on image dilation terms (%9-) and (%) .X 1 V 1Finally, liU1,V1,()1,()1] are held constant and are made to

vary to give first estimates (-9:9-) (jl) .0y 1 öx 1

The entire procedure is repeated with smaller ranges of values for (u, v) around

(L11, v1) with other values held constant as obtained from the previous iteration.

This two parameter model procedure is repeated until all the values lie within

tolerance limit.

Appendix B. Null/lERlcAL PROCEDURE Fon ¤6i=oRMATioN ANALYSIS usmc oicrrm. uviAcECORRELATION ss

START

Input :Undeformed surface dataDeformed surface dataVariable limitsTerminating limits

l Starting valueprocedure Initialize variables

Find estimates for u and v

Find estimates for QL-L and Äöx öy

Find estimates for andäy öx

IReiniatialize variable ranges

lteration .procedure Find u, V, %-, gé,

andAllowranges to converge simultaneously

Terminate the lteration when thecorrelation coefficientis acceptably small

Output :Values for u, V, Ä, Ä/-,-Qi

öx öy öyand ßl

öxvalue for the correlation coefficient

RETURN

Figure B.2. Flow diagram for correlation routine [26].

Appendix B. NUMERICAL PROCEDURE FOR DEFORMATION ANALYSIS USING DIGITAL IMAGECORRELATION 96

,Appendix C. DESCRIPTION OF MATROX6

lNote imageseg refers to 0,1,2, or 3; the 4 available image spaces on the matrox

board.

INP F12 allows to choose one of the three video inputs. lt is used by entering

|NP(imageseg). On the Matrox board input one is the top plug, two is the

center, and three is the bottom. This feature is useful to alternate

among 2 or 3 cameras coupled to the matrox board. .

CAM F2 sets the matrox board to display a live image. lt is used by entering

CAM imageseg.Th€ old image in that space is replaced by a live image

by this operation.

DIG F1 saves an image in the memory on the Matrox board. It is used by en-

IQVITIQ DIG imageseg.

I

Appendix C. DESCRIPTION OF MATROX6 SOFTWARE 97

IWIH F24 writes an image from a disk (floppy, RAM, or hard) to the Matrox board.

It is used by entering WIH imageseg (file_name). fiIe_name is the name

of the image on the disk. If the image is stored on a disk other than the

default then the disk name has to be include (i.e. ac, bz etc.),

NOTE the file name (and disk name) must be in parenthesis. This dif-

fers from WIM in that it reads images stored as HEX (using RIH) values

and the image is in two files which are AfiIe_name and BfiIe_name.

WIM F3 writes an image from a disk (floppy, RAM, or hard) to the Matrox board.

It is used by entering WIM imageseg (fiIe_name) file_name is the name

of the image on the disk. lf the image is stored on a disk other than the

default then the disk name has to be include (i.e. az, bz etc.),

NOTE the file name (and disk name) must be in parenthesis. The im-

age in the image space is replaced by the image of file_name.

RIH F23 reads an image from the Matrox board to a disk (floppy, RAM, or hard).

lt is used by entering RIH imageseg (fiIe_name) fiIe_name is the name

of where the image is to be stored on the disk. If the image is to be

stored on a disk other than the default then the disk name has to be

include (i.e. az, b: etc.), _

NOTE the file name (and disk name) must be in parenthesis. This dif-

fers from RIM in that the file is stored in HEX format and in two files

named Afile_name and BfiIe_name. This requires twice as much data

storage as the RIM.

Appendix c. ¤EscRlP1‘loN OF MATROX6 SOFTWARE 98

lRIM F23 reads an image from the Matrox board to a disk (floppy, RAM, or hard).

‘lt is used by entering RIM imageseg (file_name). file_name is the name

where the image is to be stored on the disk. lfthe image is to be stored

on a disk other than the default then the disk name has to be included

(i.e. az, bz etc.).

I

NOTE The file name (and disk name) must be in parenthesis.

IDIS F4 changes the image space being displayed by the matrox board. lt is

used by entering DIS imageseg

NOTE If a live image is being displayed changing the display will de-

stroy the old image in that space.

CUR F5 puts a cursor on the screen and can be moved to different spots using

the arrow keys. lt will work on both live and digitized images. No in-

formation is destroyed by using it on digitized images. CUR will display

the location and the gray level at the cursor center. The cursor position

can be saved to a file named "cursor.dat" by pressing the space bar.

NOTE Any old cursor.dat files will be lost. On live images the gray

level is only updated when a key is pressed. NOTE if the gray level on

a live image is needed, then without moving the cursor, press any key

other than an arrow key.U

RES F15 resets the matrox board to its original configuration.I

SYN F14 _ changes the sync source for the output from internal to external or vice

versa. lf a camera is not connected (and on) to the Matrox board and

Appendax c. DESCRIPTION OF MATROX6 SOFTWARE 99

_ I

we wish to view a digitized image we MUST enter SYN. lf later a cam-

era is connected, to view the live image SYN must be entered again.

How do we know when to enter SYN? lf the image is unstable (i.e.

rolling) then entering SYN should clear the image.

BAR F13 places a bar pattern in the memory of the Matrox board and is used to

insure your monitor is set up correctly. lt is used by entering BAR

imageseg.

NOTE Any prior image in the memory space used will be replaced by

bar pattern.

HIS F8 performs and displays a histogram of the gray levels of an image. It is

used by entering HIS imageseg.

NOTE The image will be destroyed by this process and should be

saved (using RIM or RIH ) if it is needed later. At increments of gray

levels of 50 the lines are black in the histogram.

GAN F16 sets the gain used on the input video signal. It is used by entering GAN

(x) where x is a number from 0 to 255. 0 is maximum gain and 255 is

minimum gain.

OFS F17 sets the offset used on the input video signal. lt is used by entering

OFS (x) where x is a number from 0 to 255. 255 is maximum and 0 is

minimum.

FLI F18 is to flick images. That is, two images are displayed one at a time one

Second apart and will continue to change until the < Esc> is pressed.

Appendix c. ¤EscRIPTION OF MATROX6 SOFTWARE 100

Slt is used by entering FLI (x,y) where x and y are numbers O, 1, 2, or 3

representing one of the four image spaces. x is the first to be displayed

y is the second.

AVG F11 will average incoming video images. It is used by entering AVG (x)

where x is the number of images to be averaged. x is a number be-

tween 1 and 255. lt is a very useful feature for noise reduction in the

I in-coming video signals (58).

NOTE Image space 0, 1, and 2 is destroyed by this operation. The av-

eraged image is stored in image space 0.

END F10 exits from this program back to DOS.

THI F6 is for thresholding the input video signal. lt is used by entering‘ Tl;lI(t,u,v,w), where t is the lower threshold limit and u is the gray value

U

which will be displayed. (i.e. gray levels g t will be set equal to u).

Similarly v is the upper limit and w is the gray value. ( i.e. gray levels

2 v will be set equal to w).

NOTE The image is stored in the matrox memory and original gray

levels are not available. This function works only on live images.

THO F7 is for thresholding the output video signal. lt is used by entering

THO(t,u,v,w), wheret is the lower threshold limit and u is the gray value

which will be displayed. (i.e. gray levels g t will be set equal to u).

Similarly v ls the upper limit and w is the gray value. ( i.e. gray levels

Appendax c. ¤EscRlP1'loN OF MATRox6 SOFTWARE 101

2 v will be set equal to w) lf a live image is digitized when thresholded

all gray levels are saved.

REC F22 puts a rectangle on the screen and can be moved to different spots

using the arrow keys. lt works on both live and digitized images. No

information is destroyed by using it on digitized images. REC will dis-

play the location and the gray level at the cursor center. The center

position can be saved to a file named "cursor.dat" by pressing the

space bar.

NOTE Any old cursor.dat files will be lost. On live images the gray

level is only updated when a key is pressed. NOTE if the gray level on

a live image ls needed then, without moving the cursor, pressing any”

key other than an arrow key will give the gray value.

SET F21 changes the mode ofthe PIP640 boards from 1024 to 640 mode. ln the

640 mode images are 780x512 pixels. Only 2 image spaces are avail-

able in the 640 mode.

LUT F25 changes between the 8 available look up tables. To use enter LUT x,

where x is between 0 and 7.

SYS F26 allows to enter DOS commands. To use enter SYS dos_command. Ex-

ample SYS DIR will display the contents of the current directory.

Appendix c. ¤EscRlPTloN OF MATR¤X6 SOFTWARE 102

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