atm terminal design based on fingerprint

8/12/2019 Atm terminal design based on fingerprint

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R & D PROPOSAL

RELIABLE FINGERPRINT MATCHING

SUBMITTED BY A.ROHINI

B.LALITHA DEVIP.K.SHEELA SHANTHA KUMARI


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ABSTRACT

One of the most difficult problem in humanidentification is fingerprint .

Fingerprint Matching is significantlyinfluenced by fingertip surfacecondition,which may very depending onenviromental or personal causes.


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Cont..

Minutae based matching has difficulty inquickly matching of two fingerprint images.

I proposed filter based algorithm andEucledian distance algorithm using toshow an accuracy of fingerprint matching..

Finally I showed that the ReliableFingerprint Matching is achieved by thisproject.


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Biometric Technique

Biometric is the science of verifying &establishing the identity of an individualthrough physiological features or behavioraltraits.

Physiological biometricFingerprint, Hand geometry,face,Iris.

Dependent on environmental/Interactions.


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Fingerprint Classification

Fingerprint is an impression of ridges on theskin.it can be classified in to 5 categories.

arch tented arch right loop Left loop

whorl


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EXISTING SYSTEM

The Existing system uniaueness of theridges flow pattern is the basis of forensicapplication on fingerprints,they taken small

images of fingerprint and gave solution tothe valid minutae points.


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PROPOSED SYSTEM

Fingerprint verification using EnhancedModified Direction feature and Neuralbased classification with fingerprintimages.

I proposedHow we extract the minutiae points, &How we establish whether two

` impression belong to the same finger.


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contd..

By using gabor filters size of the imagehas calculated.

By using Eucledian distance algorithm Isearch the position of ridges and to whichidentify the nearest number of ridges hastaken to calcuate distance between theridges.

Knowing the distance after that Icalculated Ridges and pore configuration.


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Features of Fingerprint Matching

Shape - Lot of variations in the shape of

minutiae. Ridges - Orientation is defined in the

ridge area.

Configuration-Measurement accuracycan be seen by comparing.


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SYSTEM ARCHITECTURE

USERINTERFACE

ENROLLMENT

MINUTAEEXTRACTOR

QUALITYCHECKER

AUTHENTICATION

MINUTAEEXTRACTOR

MINUTAEMATCHER

DATABASE

VALID/FAKE


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Cont..

Four components in architectureUser interface

System DatabaseEnrollment

Authentication


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cont The uniqueness of a configuration or ridges

depends on several factors such as whorl ,loop,arch involved in the respective of shape andsizes.

These factors matched with databse and giveauthentication to user,But sometimes notmatched in live scan process,

In my project any type of fingerprint condition isthere,it is sequentially matched and giveauthentication to user.


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MODULES

SOURCE MODULE

EXTRACTOR MODULE

MATCHING MODULE

ACCURACY MODULE

AUTHENTICATION MODULE


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SOURCE MODULE

Read Image file,The client progam isresponsible for this to provide image fortesting .


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EXTRACTOR MODULE

Fingerprint enhancement is essential toensure the robustness of fingerprintidentification with respect to the imagequality.

Gabor filter is introduced in this paper Gabor filtering is the most popular method

in fingerprint enhancement


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Cont...

The enhancement performance isassessed on standard fingerprintdatabases. Experimental results show thatthe proposed Gabor filtering method caneffectively improve the fingerprint imagequality and promote the reliability of

fingerprint identification.


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ALGORITHM

Pattern or Image based algo:Step 1: Pattern based algorithms compare

the basicfingerprint patterns (arch,whorl, and loop) between apreviously stored template and acandidate fingerprint.

Step 2: This requires that the images be

aligned in the same orientation .


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Cont Step3: The algorithm finds a central point

in the fingerprint image . Step4: In a pattern-based algorithm, the

template contains the type, size,and orientation of patterns within thealigned fingerprint image.

Step 5: The candidate fingerprint image is

graphically compared with the templateto determine the degree to which theymatch


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MATCHING MODULE

MINUTAE CONFIGURATION: When Matching is based on minutae,the

template consist of vital information aboutthese ffeatures.

{Rp,R o, R t.. R p (ME),R o (ME ), R t (ME)}R p- Ridge position

Ro-Ridge orientationRt -Type of ridgeME Minutae enrolled


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Cont..

The position gives relative to the localreference point size & shape could bestored.

Configuration = R*(1/N o)^NrR -type of RidgeNo- No,of different orientationNr-No of ridges in the configuration


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PORE CONFIGURATION

Neighboring pores are separated byconstant distance d.

D-distance between neighboring pores. Value of distance d is calculate by using

this formula

d-(area of the ridge/No .of .pores)confgtn- distance* N p* 0.48


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ALGORITHM K NN algo

Thek

-nearest neighborsalgorithm (k -NN) is a method forclassifying objects based onclosest training examples in thefeature space.


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ACCURACY MODULE

A Matching score provides the the degreeof matching between two segments with arange of complete match.

Matching score = (Minutae config value + pore config value ) * 100

2


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AUTHENTICATION MODULE

A Fingerprint is scanned and is comparedto the template in a database ,if theymatch valid finger print, If not matched it isFake.


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USER Readimage

Saveimage asidentifier

Smoothing

Filtering

Scaling

Database

Verification

Removebackgroundimages

Filtering fakeminutae

Scaling the lengthof the image

DATA FLOW DIAGRAM


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TESTING

Analyzed 20 various fingerprint imageaverage result

LIVE SCANMATCHINGSCORES 55% 54% 63%

ALGORITHM USINGMATCHING SCORE 97% 98% 99%

RING INDEX THUMB

Above 95-High accuracy (using algorithm )

50 % matching is image matched with database( ordinary live scan process)


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Experimental results

Proposed Enhancement ofalgorithm gives good results

compared with the existingsystemExperimental results showsthat the performance andefficiency are improved with

my implementation .0

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INDEX RING THUMB

LIVE SCAN SENSOR

ALGORITHM USINGWITH LIVE SCANSENSOR


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CONCLUSION

This project demonstrates an efficient fingerprintrecognition using minutiae matching, the proposedtechnique is particularly effective for verifying qualityfingerprint images, Every feature was required to matchfor the entire set to match

Proposed enhancement of algorithm for detection ofminutiae give good results in reducing the false minutiaeimprovements, due to low quality level can also refer tothe unification of image filtering and segmentationalgorithm and minutiae detection, In order to make theentire process faster


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he end

atm terminal design based on fingerprint

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