Fingerprint Verification Bhushan D Patil PhD Research Scholar Department of Electrical Engineering Indian Institute of Technology, Bombay Powai, Mumbai
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
Automated Fingerprint Identification System
Fingerprint Classification
Signatures Use signatures to determine if two fingerprints are from same finger Ridge Endings Ridge Bifurcations These are termed “minutia”
Minutiae
Minutiae Point Pattern Matching 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 Real Situation No correspondence is known beforehand There are deformations Spurious minutiae are present in templates and input images Some minutiae are missed
On-Line F.P. Verification System
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 [G x G y ]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……….