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Fingerprint Verification. Bhushan D Patil PhD Research Scholar Department of Electrical Engineering Indian Institute of Technology, Bombay Powai, Mumbai 400076. Introduction. Biometric : A human generated signal or attribute for authenticating a person’s identity
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Fingerprint Verification Bhushan D Patil PhD Research Scholar Department of Electrical Engineering Indian Institute of Technology, Bombay Powai, Mumbai 400076
Introduction • Biometric: A human generated signal or attribute for authenticating a person’s identity • Different biometric features 1.Face 2.Fingerprint 3.Iris 4.Signature 5.voice
Why Fingerprint • The advantages of using fingerprint • fingerprint identification is one of the most reliable identification technique • Its validity is justified • It is most commonly used biometrics technique • Basic Approaches Minutia Based Approach Image Based Approach
Signatures • Use signatures to determine if two fingerprints are from same finger • Ridge Endings • Ridge Bifurcations • These are termed “minutia”
Desired Information Correspondences between template and input F.P. are known There are no deformations (translations, rotation, non-linear deformations) Each minutia is exactly localized Minutiae Point Pattern Matching Real Situation • No correspondence is known beforehand • There are deformations • Spurious minutiae are present in templates and input images • Some minutiae are missed
Minutia Extraction Estimation of Orientation Field Identify fingerprint region Ridge extraction Cleaning ridge segments Minutia extraction
Estimation of Orientation Field • Orientation is the angle formed by the ridges with the horizontal axis • Find the local orientation of the ridge in small areas of the image • Steps Divide image into blocks of size WxW Compute gradients [Gx Gy]at each pixel in block Orientation at each block
Minutia Extraction • Ridge Ending • Ridge Bifurcation
Minutia Matching Point Pattern Alignment Matching Scoring
MATLAB Implementation • GUI demo……….