50409621003- fingerprint recognition system-ppt

7/15/2019 50409621003- Fingerprint Recognition System-PPT

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FINGER PRINTSRECOGNITION SYSTEM

S.ANITHALAKSHMI

50409621003



Abstract

The minutiae are ridge endings or bifurcations on thefingerprints. They, including their coordinates and

direction, are most distinctive features to represent the

fingerprint.

Most fingerprint recognition systems store only the

minutiae template in the database for further usage.

The conventional methods to utilize minutiae

information are treating it as a point set and finding the

matched points from different minutiae sets.



This kind of minutiae-based fingerprint recognition

systems consists of two steps, i.e., minutiae

extraction and minutiae matching.

In the minutiae matching process, the minutiae

feature of a given fingerprint is compared with theminutiae template, and the matched minutiae will be

found out.

The template used for fingerprint recognition isfurther utilized in the matching stage to enhance thesystem’s performance.



These templates are been stored in the database for further

processing.

Specific unique id is generated for each template stored.

The id is stored in the database along with the template locations.

Next is the verification process where you need to provide the id

for comparison.

The given id is being compared with the id’s in the database and

matched with the corresponding template of that id.



A message is being displayed on successful matching along

with the score.

Otherwise an failure message is displayed indicating match not

found.

In the identification stage we need not specify an id. Click on

the Identify button which searches for any match and provides

the corresponding result.



The database records can also be deleted through the

application.

Auto extract and Auto identify check boxes can be selected if

need which automatically extracts and identifies the matching

image

It is also possible to load an image and compare it with the

database images.

The colors of the template extraction can also be changed.



ORGANIZATIONAL PROFILE

ORATOR SOLUTIONS

The name “Orator”– A Good Speaker, One who speaks

well in public. A good speaker has lot of followers.

Like that, We people are good speaker by our work. Wesatisfy our clients by our services. And we are here to

provide Intelligent

SKILLS

Banking & Real Estate

Finance & Insurance



o Hospital and health care industry

o Web Applications

o Office Automation

o Manufacturing Retailing



HARDWARE REQUIREMENTS

Processor PENTIUM IV

RAM 128 MB

Hard Disk 40 GB



SOFTWARE REQUIREMENTS

Browser Internet Explorer

Server side scripting Java

Database Ms-Access

Client side scripting HTML



Existing System

The conventional methods to utilize minutiae

information are treating it as a point set and finding the

matched points from different minutiae sets.

In existing system, the Sparse areas are not considered.

So the result may not obtain correctly. And the

matching will be difficult to get an absolute result.



FingerPrint ViewRed SpotsMinutiae



Proposed System

In Proposed system, we considered the sparse area

and the fingerprint’s orientation field is reconstructedfrom minutiae and further utilized in the matching

stage to enhance the system’s performance.



DESIGN OF THE PROJECT



Data Flow Diagram

Show the matching Score

Thump Impression

Extract

Particular Identify

Entire Verification

Database

If Matches Show the Particular ID No

Does Not Exist

False

True

If Matches

Does not match

False

True

Enroll



Module List

Minutiae Template

Minutiae Matching

Effective Region Estimation

Orientation Field Matching

Fusing Matching



Minutiae Template

Minutiae templates are a fraction of the size of

fingerprint images, require less storage memory

and can be transmitted electronically faster than

images.



Minutiae Matching

In this module we matches the fingerprint minutiae by using both the local and global structures of minutiae.

The local structure of a minutia describes a rotationand translation invariant feature of the minutia in itsneighborhood.

It is used to find the correspondence of two minutiaesets and increase the reliability of the global matching.

The global structure of minutiae reliably determinesthe uniqueness of fingerprint. Therefore, the local andglobal structures of minutiae together provide a solid

basis for reliable and robust minutiae matching.



(a) X Person’s Fingerprint (b) X Person’s Fingerprint for

verification

Matching Stage



Effective Region ESTIMATION

we can extract the effective region by finding the

smallest envelope that contains all the minutiae

points. For an When only having minutiae feature, wecan extract the effective region by only using

minutiae illustration. Here, we put the original image

together for the convenience to give a visual sense.



Estimation of Effective Region



Orientation Field Matching

To compare two fingerprints’ orientation field, thefirst step is alignment of these two fingerprints. Thealignment is mainly based on minutiae information .Here we choose the Hough transform based approach

to finish the alignment due to its simplicity.

Hough Transform (HT) is one of the most commonmethods for detecting shapes (lines, circles, etc.) in

binary or edge images. Its advantage is its ability todetect discontinuous patterns in noisy images, but itrequires a large amount of computing power.



Fusing Matching

A variety of combination rules have been proposed. Ithas shown that matching accuracy can be improved

by combining independent matchers using Neyman –

Pearson rule. Here, we will also use Neyman – Pearson

rule for the task.

Matching of test fingerprint with template is done in

Neyman-Pearson rule. Two sets of minutiae are

compared. If matching score is found, then thefingerprint is matched with template. Otherwise does

not matched with the template.



Input And Output Screens



Main Page



Authentication

L d BMP I



Load BMP Image



Extract Template

Enroll



Enroll



R t



Reports



Verify



Identify



Identify

ClearDatabase



Clear Database

Clear Log



g



Benefits of the project

The project can be used for security purposes.

E.g. : Attendance ,voter registration,

Crime Investigation,

forensic fingerprint searching.

CONCLUSION



CONCLUSIONOrientation field is important for fingerprint

representation. In order to utilize the orientationinformation in automatic fingerprint recognition

systems which only stores minutiae feature. So we can

reduce the usage of memory and enhancing the

performance of system.

We also utilize the reconstructed orientation field

information into the matching stage. We can reducethe effect of wrongly detected minutiae. A fingerprint

matching based on orientation field is used to combine

with conventional minutiae matching for real

applications.



THANK YOU

50409621003- fingerprint recognition system-ppt

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