# Fingerprint Verification Bhushan D Patil PhD Research Scholar Department of Electrical Engineering Indian Institute of Technology, Bombay Powai, Mumbai.

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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

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……….

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