lec15 Finger Print Recognition-III

# lec15 Finger Print Recognition-III - Fingerprint...

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CSE190a Fall 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 • Let ( ) ( ) { } P M P M P M P P P y x y x P θ θ , , ,..., , , 1 1 1 = be the set of M minutiae in the template image • Let ( ) ( ) { } Q N Q N Q N Q Q Q y x y x Q θ θ , , ,..., , , 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
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