major porject report (1)

7/24/2019 Major Porject Report (1)

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Integrated Daylight Harvesting And Human Detection Using Digital Image Processing

CHAPTER 1

INTRODUCTION

Daylight harvesting in commercial buildings is experiencing renewed interest,

particularly in light of the environmental consequences of power generation, the desire for

sustainable design, and current strains on the nations power grid. It has been estimated that

commercial businesses use one-quarter of their total energy consumption for lighting.

Daylighting and its associated systems, therefore, offer the opportunity to reduce energy

consumption and costs.

Estimates show that between !" and #!" of the spaces in commercial buildings has

access to daylight either through windows or s$ylights. %he installation of technologiesdesigned to ta$e advantage of available daylight would be an appropriate energy-saving

strategy that could potentially turn off millions of light fixtures for some portion of each day.

& number of technologies currently on the mar$et are designed to either reduce

energy use from electric lighting or increase the daylight penetration within a building while

controlling glare. %he energy-reducing systems typically employ a photosensor technology

teamed with a dimming fluorescent lighting system, which reduces energy demand by

dimming lights proportionally to the amount of daylight received at a reference plane.

'nfortunately, most of these systems do not guarantee effective operation because daylight

rarely penetrates uniformly into a buildings interior. Daylight penetration can vary at

ad(acent wor$stations because individuals operate blinds or exterior obstructions bloc$

daylight. &dditionally, each photosensor typically controls a number of light fixtures in a

space, often resulting in areas that are too dar$ and others that are over-lighted. )igh initial

costs for full dimming ballasts and difficulties with installing and commissioning

photosensors also impede the installation of these systems in commercial buildings.

*ystems that improve daylight penetration include light shelves, light pipes,

controlled shades and blinds, and other active sun-trac$ing daylight delivery systems. &gain,

most of these technologies involve high initial and maintenance costs.

+roblems with current daylighting systems combined with poor sales, point to the

need for new designs that are simple, low cost, and effective. &n effective way to address this

energy problem is to deploy automatic lighting control systems.

%his pro(ect describes a proof-of-concept implementation that uses a high dynamic

range * video camera to integrate daylight harvesting and human detection

Department of ENC Usha Mittal Institute of Technology1


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functionalities. It can be demonstrated that the proposed concept not only overcomes several

drawbac$s of conventional lighting control sensors, but also offers functionalities that are not

currently achievable by these sensors.

+roposed concept involves three algorithms, daylight estimation, occupancy detection

and lighting control. %he calibrated system directly estimates luminance from digital images

of the occupied room for use in the daylight estimation algorithm. & novel occupancy

detection algorithm involving color processing in / space and 0ounding 0ox has been

developed. ur lighting control algorithm is based on the 1* technique. 1esults show that2

i3 *ystem can meet different target light-level requirements for different tas$ areas

within the field-of-view of the sensor

ii3 *ystem is unaffected by direct sunlight or a direct view of a light source

iii3 It detects very small movements within the roomiv3 *ystem allows real-time energy monitoring and performance analysis.



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CHAPTER 2

LITERATURE SURVEY

2.1 Occupancy sensors and !e"r dra#$ac%s

4ith typical energy savings ranging from #5" - #6" for classrooms and 56"-6"

for private offices, occupancy sensors are often viewed as one of the most energy and cost-

effective lighting control technologies. )owever, even after being around for over 5! years,

occupancy sensors do not have as high mar$et penetration as some other building

technologies, partly due to the difficulty in definitively predicting and demonstrating savings.

ccupancy sensor performance is also dependent on the user occupancy, lighting control

patterns, sensor selection and finally, commissioning, leading to varied savings estimates by

the industry. 1ecent research has shown that reducing the time delay in the occupancy

sensors can increase the energy savings in spite of a potential increase in lamp maintenance

cost due to higher switching frequency. It has been found that the activity level is different for

different users of a common space and even changes over the time of the day for a given user.

)owever, a typical occupancy sensor only allows a single time delay setting based on

the application, which can vary from several seconds to more than ! minutes, and remains

constant once set. %he time delay is commonly maintained at a higher level than necessary to

minimi7e false offs 8when no motion is detected in presence of occupancy3, thus reducing

energy savings. nce calibrated, the sensitivity of the device to room movement cannot be

changed as well. ost occupancy sensors used in commercial applications use passive

infrared or ultrasonic motion-sensing technologies. any use dual technologies, which

combine the two technologies or others, such as microwave, in one sensor.

2.2 P!oosensors and !e"r dra#$ac%s



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In comparison to occupancy detection, daylight harvesting is a significantly less

successful and somewhat less popular lighting control strategy. %he use of photosensors to

control interior lighting is nontrivial. *ince a photosensor signal greatly depends on the

position of the sensor relative to room surfaces and daylight apertures, as well as room

surface material properties, commissioning and calibration play a pivotal role in photo sensor

applications. 9arious problems associated with calibration and commissioning contribute to

the fact that photo sensor-based systems have seen limited application and have traditionally

faced mar$et barriers.%hus, there is a need for an advanced daylight sensor that can reap the

benefits and flexibility that these technologies offer and achieve a better control of the light

distribution within a space,improving the overall light quality.

2.& An "'a(e sensor&n image sensor can be thought of as a cluster of photosensors. 'nli$e photosensors,

they do not give us a single electrical signal, but rather provide luminance as well as colour

information at thousands of points within the space. & sequence of digital images of the space

thus gives us a wealth of information that we can use to estimate daylight availability in

various parts of the space simultaneously, as well as detect occupancy. %han$s to the

tremendous growth and development in * technology, today digital imaging is

pervading every sphere of our life, providing us with cost-effective and innovative solutions.

1ecently, high dynamic range * video sensors have been introduced in the

mar$et, primarily for various automotive applications, whose technical constraints are

somewhat similar to those of interior lighting applications. In both cases, the imaging system

needs to wor$ under a wide dynamic range, have a fast but affordable image processing

functionality, and finally, have integrated image acquisition and image processing modules

that continuously interact with each other. 1eal-time operation might involve ad(usting the

image acquisition system based on the lighting condition. )owever, the lighting product will

have a more stringent budget constraint than a product for an automotive application. )ere,

by automotive applications we mean lane recognition, par$ing control, obstacle:traffic sign

recognition etc.

2.) Proposed Concep



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%he fundamental hypothesis of this pro(ect is that we can use an image sensor for

daylight harvesting and occupancy sensing at the same time, but more importantly, for

developing a lighting control system that is more versatile and that offers a far better control

of the illuminated environment. ur approach is significantly different from the prior image

sensor based lighting control devices. %he pro(ect also overcomes several drawbac$s of

conventional lighting control sensors. In addition, an integrated sensor can provide

functionalities that are impossible to achieve by conventional photosensors and occupancy

sensors.

;or human detection various methods have been proposed in the past years.

0ac$ground subtraction is often used to detect moving ob(ects from a video ta$en by a

stationary camera. aintaining the bac$ground adaptively in accordance with illumination

changes is the $ey issue in this approach. )umans can also be detected and trac$ed by using

related information such as edges, colour, and depth. ethods using colour would encounter

a difficulty when the bac$ground contains some ob(ects with similar colour - trac$ing could

be misguided by bac$ground clutters.

CHAPTER &



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PRO*ECT DESCRIPTION

&.1 +,oc% D"a(ra'

-"(ure &.1 +,oc% d"a(ra'.

%he basic concept of this pro(ect is we use an image sensor for daylight harvesting

and occupancy sensing at the same time, but more importantly, for developing a lighting

control system that is more versatile and that offers a far better control of the illuminated

environment. 4e use a * camera to acquire a reference image. %his reference image is

first converted to gray image which is used in the occupancy detection algorithm. %hen weconvert the reference image to


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turned on, or if the value is greater than the maximum preset level then the lights are turned

off. %he control signals from the parallel port are sent using parallel port command given in

&%>&0.

%he parallel port is connected to driver uln5!!. 4henever the output from the

parallel port is high the driver I will ground its output terminals and whenever the output

from the parallel port is low, then the I will give a ?@5v at its output pins. 4hen the output

pins of the I is @5v the potential across the relay connected to it at one end and a @5v supply

at other end will be !v, thereby turning off the lights. 4hen the output of the I is !v then the

potential across the relay is @5v which turns on the lights. %hus, the driver I drives the @5v

relays connected to it which in turn, turns on or turns off the lights.

&.2 A,(or"!'

&.2.1 Occupancy Deec"on

ccupancy detection is done using 5 procedures.

Procedure 12

;irst, absolute / image difference between the last frame and the current frame is

computed. %he last two components of / contain chromatic information independent of

the intensity. %hese are used to derive an rms difference metric as per equation below.

4here, 8b@, r@3 are the chromatic components at a given pixel in the last frame,

and 8b5, r53 are the corresponding values in the current frame. %he metric is simply the

Euclidean distance in the b - r plane. %he difference image 8pixel differences between any

frame and the reference frame3 and the thresholds are based on this metric. %here are two user

specified thresholds, one for the pixel difference, and one for the spatial extent 8in terms of a

fraction of total number of pixels in a frame3. %hese thresholds are programmable, thus

allowing a real-time ad(ustment to the motion sensitivity of the sensor based on the operating

requirements. %he detection area is controlled through the specification of regions of

interests, otherwise the whole frame is considered.

*econdly, the detection of changes between frames is more robust against pixel noise.

%he pixel noise is li$ely to be introduced during various stages of the processing chain,

including compression and transmission, and is predominantly present in the intensity



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channel. %his metric is also less li$ely to be seriously affected by minor changes in the space

illumination level than a metric based on raw 1A0 values. %his is convenient because a

change in the light level in the space does not typically cause a false alarm, unless the change

is significant. ;inally, this method is fast and inexpensive, which is a critical requirement for

this application.

Procedure 2

'sing the procedure of gray scale difference of current and reference frame and

scaling the values using im5bw8 3 command and plotting for the motion blobs in the image

using the concept of bounding box using rectangle command.

&.2.2 L"(!"n( Conro,

>ights are controlled using relays 8@5v type3 with the help of parallel port controlled

by the &%>&0 command. &ccording to the motion detection and brightness test Bpval8 3

value is sent to parallel port.

&.& -,o# c!ar



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&.&.1 Re/erence /ra'e

&.&.2 Occupancy Deec"on


Sar

Initiali7e &%>&0 C

image acquisition device

%a$e reference

image

onvert 1A0 toAray8Bb3 C /rb

Divide the image to four

segments

alculate the 1* value of each segment, save it

from B1*@ through B1*=

onvert the image to


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>oad B1*@ through

B1*= and load Bb

C

%a$e a new

frame Bi@

Initiali7e the parallel port

8pvalF! ! ! ! ! ! ! !G3

onvert Bi@ to /rb colour space

and divide it into = segments

alculate the 1* value of each segment,

save it from B1*@@ through B1*=@

%a$e the difference between the corresponding segments

1* values C save it in Bimd@ through Bimd=

onvert Bi@ to gray 8Ba3

Ba difference Bb

onvert gray image Bc into binary

image B04 with th !.@

A

A


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Divide the binary images into = segments Bx@

through Bx=

Initiali7e ovectF G

;or each segments, if there is a difference, draw the bounding

box using Bregionprops and rectangle commands

If imd of any

segH th yes no

orresponding seg value

of ovect FG!

orresponding seg value

of ovect FG@

yesIf motion in any seg no

'pdate the frame as reference

frame 8ba3

+

C

+


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CHAPTER )


>oad mlevel@ C mlevel5

>oad brightness@ through

brightness=


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SO-T0ARE DESCRIPTION

).1 ATLA+ S"'u,"n% .3.45R2446a7

&%>&0 is an integrated technical computing environment that combines numeric

computation, advanced graphics and visuali7ation, and a high level programming language.

&%>&0 includes hundreds of functions for2

Data analysis and visuali7ation


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& colour space is a means of uniquely specifying a colour. %here are a number of

colour spaces in common usage depending on the particular industry and:or application

involved. ;or example as humans we normally determine colour by parameters such as

brightness, hue, and colourfulness. n computers it is more common to describe colour by

three components, normally red, green, and blue. %hese are related to the excitation of red,

green, and blue phosphors on a computer monitor. &nother similar system geared more

towards the printing industry uses cyan, magenta, and yellow to specify colour, they are

related to the reflectance and absorbance of in$s on paper.

%here are generally ways of converting 8transforming3 between different colour

spaces although in most cases the transformation is nonlinear. *ome colour spaces for

example can represent colours which cannot be represented in others.

).&.2 R8+ co,our cu$e

%he colour space for computer based applications is often visuali7ed by a unit cube.

Each colour 8red, green, blue3 is assigned to one of the three orthogonal coordinate axes in

D space. &n example of such a cube is shown below along with some $ey colours and their

coordinates.

-"(ure ).1 R8+ co,or cu$e



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&long each axis of the colour cube the colours range from no contribution of that

component to a fully saturated colour.

%he colour cube is solid, any point 8colour3 within the cube is specified by three

numbers, namely, an r, g, b triple.

%he diagonal line of the cube from blac$ 8!,!,!3 to white 8@,@,@3 represents all the

grays, that is, all the red, green, and blue components are the same.

In practice different computer hardware:software combinations will use different

ranges for the colours, common ones are !-5#N and !-N##N for each component. %his

is simply a linear scaling of the unit colour cube described here.

%his 1A0 colour space lies within our perceptual space, that is, the 1A0 cube is

smaller and represents fewer colours than we can see.

4.3.3 Grayscale Images

& grayscale 8or gray level3 image is simply one in which the only colors are shades of

gray. %he reason for differentiating such images from any other sort of color image is that lessinformation needs to be provided for each pixel. In fact a OgrayP color is one in which the red,

green and blue components all have equal intensity in 1A0 space, and so it is only necessary

to specify a single intensity value for each pixel, as opposed to the three intensities needed to

specify each pixel in a full color image.

ften, the grayscale intensity is stored as an 6-bit integer giving 5#N possible different

shades of gray from blac$ to white. If the levels are evenly spaced then the difference

between successive gray levels is significantly better than the gray level resolving power of

the human eye.

Arayscale images are very common, in part because much of todayPs display and

image capture hardware can only support 6-bit images. In addition, grayscale images are

entirely sufficient for many tas$s and so there is no need to use more complicated and harder-

to-process color images.



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).&.) Con:ers"on

I rgb5gray81A03

I rgb5gray81A03 converts the true color image 1A0 to the grayscale intensity image

I. rgb5gray converts 1A0 images to grayscale by eliminating the hue and saturation

information while retaining the luminance.

).) YC$Cr

& color space is simply a model of representing what we see in tuples. /br is one

of the popular color space in computing. It represents colors in terms of one luminance

component:luma 8/3, and two chrominance components:chroma 8b and r3. *tudy shows

human eyes are sensitive to luminance, but not so sensitive to chrominance. ;or example,

given an image below,

-"(ure.).2 A co,our "'a(e.

%he /br image can be converted to:from 1A0 image. %herere several standards

defined for the conversion at different context. %he conversion below is based on the

conversion used in Q+EA image compression.

%he conversion can be expressed as equations below.



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;rom 6-bit 1A0 to 6-bit /br2

%he /, b and r components can be observed as shown in the ;igure =.5.

-"(ure.).& Co,or I'a(es /or'ed $y Y; C$ and Cr Co'ponens

).< +ound"n( +o= "n ATLA+

In0ounding 0ox method input is a binary image, and output is another binary image

holding the rectangles over the detected blobs. It is not a superimposition of a rectangle over

an image.

1E%&E command draws the bounding boxes around the blobs in a binary

image, image is the binary image input supplied by the user. %his function extracts the

coordinates and dimension values of each blob from stats. 0ounding 0ox structure one by

one and draws the rectangle around them.

Edata@ regionprops8x5, P0ounding0oxP3

[email protected]@33R

[email protected]

[email protected]

[email protected]=33R

rectangle8P+ositionP,FEx5,Ey5,Ew5,Eh5G,PEdgeolorP,PrP3R

[email protected] 8@3 gives the x dimension



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[email protected] 853 gives the y dimension

[email protected] 83 gives the height

[email protected] 8=3 gives the width

Recan(,e

reate 5-D rectangle ob(ect

Syna=

rectangle

rectangle8P+ositionP,Fx,y,w,hG3

Descr"p"on

rectangle8P+ositionP,Fx,y,w,hG3 draws the rectangle from the point x,y and having a width of w

and a height of h. *pecify values in axes data units.

).3 8rap!"ca, User Iner/ace

& graphical user interface 8A'I3 is a pictorial interface to a program. & graphical user

interface 8A'I3 is a graphical display in one or more windows containing controls, called

components that enable a user to perform interactive tas$s. %he user of the A'I does not have

to create a script or type commands at the command line to accomplish the tas$s.

A'I components can include menus, toolbars, push buttons, radio buttons, list boxes,

and slidersS(ust to name a few. A'Is created using &%>&0 tools can also perform any

type of computation, read and write data files, communicate with other A'Is, and display

data as tables or as plots. )ere the inputs are $nown as events, and a program that responds to

events is said to be event driven.

%he three principal elements required to create a &%>&0 Araphical 'ser Interface are2

1. Co'ponens.Each item on a &%>&0 A'I 8pushbuttons, labels, edit boxes, etc.3 is a

graphical component. %he types of components include graphical controls 8pushbuttons, edit

boxes, lists, sliders, etc.3, static elements 8frames and text strings3, menus, and axes.

Araphical controls and static elements are created by the function uicontrol, and menus are

created by the functions uimenu and uicontextmenu. &xes, which are used to display

graphical data, are created by the function axes.



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2. -"(ures.%he components of a A'I must be arranged within a figure, which is a window

on the computer screen. In the past, figures have been created automatically whenever we

have plotted data. )owever, empty figures can be created with the function figure and can be

used to hold any combination of components.

&. Ca,,$ac%s.;inally, there must be some way to perform an action if a user clic$s a mouse

on a button or types information on a $eyboard. & mouse clic$ or a $ey press is an event, and

the &%>&0 program must respond to each event if the program is to perform its function.

;or example, if a user clic$s on a button, that event must cause the &%>&0 code that

implements the function of the button to be executed. %he code executed in response to an

event is $nown as a call bac$. %here must be a callbac$ to implement the function of each

graphical component on the A'I.

8UIDE, the &%>&0 Araphical 'ser Interface Development Environment, provides

a set of tools for creating graphical user interfaces 8A'Is3. %hese tools greatly simplify the

process of laying out and programming A'Is. %he A'IDE >ayout Editor enables you to

populate a A'I by clic$ing and dragging A'I components into the layout area. %here you

can resi7e, group and align buttons, text fields, sliders, axes, and other components you add.

8UI A,,o#s On,y One Insance o Run 5S"n(,eon7.

%his option allows you to select between two behaviors for the A'I figure2

&llow &%>&0 software to display only one instance of the A'I at a time.

&llow &%>&0 software to display multiple instances of the A'I.

If you allow only one instance, the software reuses the existing A'I figure whenever

the command to run the A'I is issued. If a A'I already exists, the software brings it to the

foreground rather than creating a new figure. If you clear this option, the software creates a

new A'I figure whenever you issue the command to run the A'I. If we allow only one

instance of a A'I to run, initiali7ation can ta$e place each time we call it from the command



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line.

-"(ure ).) P,a"n 8UI

CHAPTER 12



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NO


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duty cycle depending on ambient temperature and number of drivers turned ED and incandescent displays, and heaters. &ll devices feature open-collector

outputs with integral clamp diodes. %he '> or *. %hese devices will handle numerous interface

needs S particularly those beyond the capabilities of standard logic buffers. %he '>


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+ins @6-5# are grounds and are used as a reference signal for the low 8below !.# volts3

charge.

-"(ure


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-"(ure


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regulator. %here are variants on the V6xx series Is, such as V6> and V6*, some of which can

supply up to @.# &mps.

Na'e Vo,a(e

>V6!# ? # volts

>V6!L ? L volts

>V6@5 ? @5 volts

>VL!# - # volts

>VL!L - L volts

>VL@5 - @5 volts

-"(ure V6WWM series of voltage regulators are designed for positive input. ;or

applications requiring negative input the M>VLWWM series is used.

-"(ure V6@5 of three terminal positive regulators are available in the %-55!

pac$age and with several fixed output voltages, ma$ing them useful in a wide range of

applications. Each type employs internal current limiting, thermal shut down and safe

operating area protection, ma$ing it essentially indestructible. If adequate heat sin$ing is

provided, they can deliver over @& output current. &lthough designed primarily as fixed

voltage regulators, these devices can be used with external components to obtain ad(ustable

voltages and currents.


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utput urrent up to @&

utput 9oltages of @5 volt

%hermal verload +rotection

*hort ircuit +rotection

utput %ransistor *afe perating &rea +rotection

CHAPTER 3

E?PERIENTAL PROCEDURE RESULTS

STEP 1 Inpu "'a(e /ro' #e$ca'

@. apture image from webcam.

:o$ B :"deo"npu5#"n:"deo;1;YUY23)4=)647

pre:"e# 5:o$7

"' B (esnaps!o5:o$7

)ere,

:"deo"npu >specifies the adaptor name and resolution.

%he above instruction is of the type,

o$ B :"deo"npu5 adaporna'e ; de:"ceID ;/or'a 7



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adaporna'eis a text string that specifies the name of the adaptor used to communicate

with the device.

de:"ceID is a numeric scalar value that identifies a particular device available through the

specified adaptor, adaptor name

/or'ais a text string that specifies a particular video format supported by the device or

the full path of a device configuration file 8also $nown as a camera file3.

pre:"e# 5o$7creates a 9ideo +review window that displays live video data for video

input ob(ect ob(. %he window also displays the timestamp and video resolution of each

frame, and the current status of ob(. %he 9ideo +review window displays the video data at

@!!" magnification 8one screen pixel represents one image pixel3.

/ra'e B (esnaps!o5o$7immediately returns one single image frame, frame, from the

video input ob(ect ob(.

5. *tore the captured image into an image file for further processing.


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-"(ure 3.1 Re/erence "'a(e

STEP 2 o"on Deec"on

@. onvert image into grayscale.

"'1Br($2(ray5"'7

)ere, rgb5gray converts color image to gray scale image. im@ will have the gray image.



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-"(ure 3.2 8ray "'a(e

5. alculate absolute difference value for the image current and reference frames.

cB"'a$sd"//5a;$7

. Entire image is segmented into four equal parts which is done as follows

/"(ure517;

=1B=512)4;1&24;7



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su$p,o52;2;17;"'s!o#5=17

=2B=512)4;&213)4;7

su$p,o52;2;27;"'s!o#5=27

=&B=52)1)64;1&24;7

su$p,o52;2;&7;"'s!o#5=&7

=)B=52)1)64;&213)4;7

su$p,o52;2;)7;"'s!o#5=)7

-"(ure 3.& 8ray "'a(e d":"ded "no /our se('ens

=. onvert the image into binary image using the calculated threshold.

"'2 B "'2$# 5c; !res!o,d7

)ere, im5bw command converts the image given to it into blac$ and white depending

on the threshold value.



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-"(ure 3.) D"//erence "'a(e

#. 0ounding 0ox2

In0ounding 0ox method input is a binary image, and output is another binary image

holding the rectangles over the detected blobs.

Edaa1 B re("onprops5=2; +ound"n(+o=7

E=2B5Edaa1.+ound"n(+o=5177

Ey2B5Edaa1.+ound"n(+o=5277

E#2B5Edaa1.+ound"n(+o=5&77

E!2B5Edaa1.+ound"n(+o=5)77

recan(,e5Pos""on;FE=2;Ey2;E#2;E!2G;Ed(eCo,or;r7

%hese rectangles when plotted on a colored image will result in as follow.



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-"(ure 3.< o"on deec"on

STEP & +r"(!ness deec"on

@. onvert image into grayscale.

I'2Br($2nsc5"'7

)ere, rgb5ntsc converts color image to


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-"(ure 3.3 NTSC se('ened "n /our /ra'es

5. alculate appropriate threshold value for the image.

!res!o,d B (ray!res!5"'27

)ere, the brightness of the is the level above which the lights should off.


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;or initiali7ing the parallel port the following commands are used2

1. DIO B d"("a,"o5adapor;ID7

PadaptorP-%he hardware driver adaptor name. %he supported adaptors are advantech, $eithley,

mcc, nidaq, and parallel. 4e have made use of the adaptor name parallel.

ID-%he hardware device identifier. %he toolbox provides basic DI capabilities through the

parallel port. %he + supports up to three parallel ports that are assigned the labels >+%@,

>+%5, and >+%. ost +s that support the &%>&0 software will include a single parallel

port with label >+%@.

DI-%he digital I: ob(ect.

Descr"p"on

DI digitalio8PadaptorP,ID3 creates the digital I: ob(ect DI for the specified adaptor and

for the hardware device with device identifier ID.

So;

parporBd"("a,"o5para,,e,;LPT17

reates the digital I: ob(ect parport for adaptor parallel, and parallel port used is >+%@.

2. ,"nes B add,"ne5o$;!#,"ne;d"rec"on7

ob(-& digital I: ob(ect.

hwline-%he numeric IDs of the hardware lines added to the device ob(ect.

PdirectionP-%he line directions can be In or ut, and can be specified as a single value or a cell

array of values.

lines-& column vector of lines with the same length as hwline.

Descr"p"on



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lines addline8ob(,hwline,PdirectionP3 adds the hardware lines specified by hwline to the

digital I: ob(ect ob(. direction configures the lines for either input or output. lines is a row

vector of lines.

So;

,"neBadd,"ne5parpor;4;ou7

&dds eight lines 8!2V3 to parport from port !, it acts as an output lines.

&. p:a, B F4 4 4 4 4 4 4 4G

reates a matrix of si7e @ by 6 with all the initial values 7ero.

). pu:a,ue5o$;daa7

ob(-& digital I: ob(ect.

data-& decimal value or binary vector.

Descr"p"on

putvalue8ob(,data3 writes data to the hardware lines contained by the digital I: ob(ect ob(.

So;pu:a,ue5parpor;p:a,7

It is used to transfer pval value to parallel port.

;or initiali7ing the parallel port >+%@ the commands are executed in the following order.

parportdigitalio8PparallelP,P>+%@P3R

lineaddline8parport,!2V,PoutP3R

pval F! ! ! ! ! ! ! !GR

putvalue8parport,pval3R



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STEP


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-"(ure 3.6 8UI /or re/erence /ra'e

4e need to give values of IE9E> and &W>E9E> for which the lights

should be on:off. &fter writing in appropriate values in edit box we need to press the X

button which will load these two values.



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o"on p,oed 8UI and ,"(! saus

4hen 1'< button is pressed the motion plotted image appears on the left side and

difference image on the on the right, corresponding status of the light is displayed on the

>IA)% *%&%'* edit boxes.

-"(ure 3.@ o"on p,oed and ,"(! saus

%he additional buttons li$e *%+ will stop the execution and close the A'I.

%he EWI% button is used to exit and close all &%>&0 windows.



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CHAPTER

ADVANTA8ES

;ollowing are some advantages offered by the proposed solution over conventional systems2

& single sensor can function as a photosensor as well as an occupancy sensor.

& single sensor can be used for different tas$ areas 8or control 7ones3 with different

target light level requirements, as long as the sensor has a view of all tas$ areas. &

conventional system will typically need several photosensors for this purpose.

ompared to a conventional photosensor, the performance of the proposed system is far

less li$ely to be adversely affected by a direct view of a light source or direct sunlight.

%he sensor is capable of detecting small movements, on the order of a couple of inches,

several feet away from the camera as long as it has an adequate resolution. %he sensor

sensitivity to motion can be ad(usted in real-time based on the activity level or other

criteria. &s such, this approach can offer a better capability in occupancy detection

compared to conventional occupancy sensors.

&lgorithms can be developed so that the problem of people or ob(ects partially bloc$ing

the sensors view of the tas$ areas can be circumvented.

1eal-time energy monitoring and performance analysis of the actual system is possible,

which is unique to this application.

* %echnology can provide an attractive and cost effective solution.

CHAPTER 6



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APPLICATIONS

Co''erc"a, and do'es"c $u",d"n(sommercial buildings use air conditioning and increasingly use curtain wall design

with single gla7ing. Estimates show that between !" to #!" of the spaces in these

buildings has access to daylight through windows and doors but these buildings

completely rely on artificial lightning with very less use of natural daylight. %his problem

can be solved using daylight harvesting.

%he system detects the daylight and human presence and switches on the lights as per

need. %hus, the regions where there is no need of artificial lights and where the natural

sunlight can be made use of, the system provides an efficient way of using natural energy.

%his can be achieved using same cameras and pcs used for surveillance purpose.

%his method overcomes several drawbac$s of conventional sources used in daylight

harvesting and provides additional functionalities which are not achievable by these

sensors, thus significant amount of energy can be saved.

Tra//"c ,"(! conro,'sing the surveillance cameras installed to chec$ the trafficR this algorithm can be

used to automatically control the traffic lights depending on the traffic density. %hus this

method provides an efficient way of controlling traffic.

CHAPTER @

CONCLUSION



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In our pro(ect we are able to control the lights of a room combining the daylight

estimation, occupancy detection and the lighting control algorithms. 4e are able to detect the

smallest change in the acquired image from the new image, which ma$es it very efficient.

Implementation of our pro(ect in commercial and domestic buildings will save a lot of

power, which otherwise is wasted because of the use of artificial lightings, thereby ma$ing

optimum use of the natural light from sun. %hus we are able to ma$e use of the natural

sunlight rather than the artificial lights which is the main ob(ective of our pro(ect, which

cannot be obtained using the conventional sensor methods. %hus this system can be helpful in

saving electricity and ma$ing the area energy efficient. In our pro(ect we control the lights in

the room, but other than controlling the lights we can also design it to control different

electrical appliances li$e fan, air conditioner etc. Due to its easy implementation and user

friendly A'I, we believe this pro(ect is a boon for the commercial as well as the domestic

buildings.

*pecular reflection from daylight can cause the prototype to overestimate illuminance

in locali7ed areas. %o counter this, existing algorithm needs to be improved and a suitable

calibration and commissioning procedure must be outlined. Dar$ surfaces typically have low

luminance, thus signal-to noise ratio becomes an issue in estimating tas$ illuminance on dar$

surfaces.

major porject report (1)

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