lec15 Finger Print Recognition-III

lec15 Finger Print Recognition-III - Fingerprint...

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CSE190a Fal 06 Finger Print Recognition (RANSAC) and back to Face Rec Biometrics CSE 190-a Lecture 15 © Jain, 2004 Fingerprint Representation Fingerprint Representation • Local ridge characteristics ( minutiae ): ridge ending and ridge bifurcation • Singular points: Discontinuity in ridge orientation Core Delta Ridge Ending Ridge Bifurcation © Jain, 2004 Minutiae Correspondences Minutiae Correspondences © Jain, 2004 Minutiae Matching Minutiae Matching • Point pattern matching problem •Le t ( ) ( ) { } P M P M P M P P P y x y x P θ , , ,..., , , 1 1 1 = be the set of M minutiae in the template image •L e t ( ) ( ) { } Q N Q N Q N Q Q Q y x y x Q , , ,..., , , 1 1 1 = be the set of N minutiae in the input image • Find the number of corresponding minutia pairs between P and Q and compare it against a threshold © Jain, 2004 Stages of Minutiae-based Verification • Extract Minutiae using corner detection • Characterize (label) Minutiae • Transformations between fingerprint images •RANSAC CSE152, Spr 05 Intro Computer Vision Convolution: R= K*I I R ∑∑ =− = = 2 / 2 / 2 / 2 / ) , ( ) , ( ) , ( m m h m m k k j h i I k h K j i R Kernel size is m+1 by m+1 m=2
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CSE152, Spr 05 Intro Computer Vision exp x 2 + y 2 2 σ 2 An Isotropic Gaussian • The picture shows a smoothing kernel proportional to (which is a reasonable model of a circularly symmetric fuzzy blob) CSE152, Spr 05 Intro Computer Vision On numerical derivatives Convolve with First Derivative: [-1 0 1] Second Derivative: [-1 2 -1] First Derivative in Y Direction:[-1 0 1] T CSE152, Spr 05 Intro Computer Vision Smoothing and Differentiation • Need two derivatives, in x and y direction.
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This note was uploaded on 02/14/2008 for the course CSE 190A taught by Professor Kriegman during the Fall '06 term at UCSD.

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lec15 Finger Print Recognition-III - Fingerprint...

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