08-Biometrics-Lecture8-Day2-Part2-16-00-17-30

08-Biometrics-Lecture8-Day2-Part2-16-00-17-30 - Continuing...

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1 Biometric Identity Verification http://scgwww.epfl.ch/courses Continuing Education – COST 2101 Training School Dr. Andrzej Drygajlo Speech Processing and Biometrics Group Signal Processing Institute Ecole Polytechnique Fédérale de Lausanne (EPFL) Center for Interdisciplinary Studies in Information Security (ISIS)
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2 Face Speaker Recognition Dynamic Signature Fingerprints Iris Hand Others Leading Biometric Technology
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3 Identifiable biometric characteristics Biological traces DNA (DeoxyriboNucleic Acid), blood, saliva,etc. Biological (physiological) characteristics fingerprints , eye irises and retinas, hand palms and geometry , and facial geometry Behavioral characteristics dynamic signature , gait, keystroke dynamics, lip motion Com bined voice
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4 Popular biometric characteristics (modalities) Fingerprint Voice Signature Face Iris Hand
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5 Comparison of biometric techniques ACCURACY COST Fingerprint Vo ice / Speech Signature Fa ce Hand Iris
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6 Hand The human hand contains a wide variety of measurable characteristics that can be used by biometric authentication systems. Typical visible images of a) palmar b) lateral c) dorsal surfaces of the hand scanner < 180 dpi low/medium-resolution CCD camera
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7 Dorsal surface Visible image Thermal image Hand-geometry (shape) Vein patterns (dorsal veins) - biometric features - aliveness features Visible and Thermal Images
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8 Hand geometry and Hand palm Hand geometry Hand palm
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9 Palmar Surface Hand shape Fingerprints Palm print Finger strips (digitprints) Palmar veins
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10 References (DNA) R.L. Zunkel, “ Hand Geometry Based Verification ”, chapter 4 in A. Jain, R. Bolle, S. Pankanti, “ Biometrics: Personal Identification in Networked Society ”, Kluwer Academic Publishers, Norwell, 1999. A. K. Jain, A. Ross, S. Pankanti, “A Prototype Hand Geometry-based Verication System”, 2nd Int. Conf. on Audio- and Video-based Biometric Person Authentication (AVBPA), Washington, March 1999, pp. 166-171.
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11 Why Hand Geometry? Geometric features: Bone structure remains constant beyond a certain growth period People’s ease of acceptance due to convenience Image acquisition is easy Easy and cheap setup Good performance on a medium sized database A good tradeoff between cost and level of security of the application
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12 Pegged v/s Peg-less Systems
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13 Pegged v/s Peg-less Systems Pegged Systems Pros: Predefined axis to measure features along Cons: Pegs may deform shape –> results may be sub-optimal Different placement of fingers may result in greater variability in features measured along fixed axis Peg-less Systems Pros: More robust than Pegged Systems to tolerate different placement of palm/fingers Cons: Challenging to locate the axis along which to measure the features
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Hand Geometry Measurements Features: dimensions and shape of the hand, fingers, and knuckles as well as their relative locations. Two images taken: one from the top and one from the
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This note was uploaded on 06/25/2009 for the course MATH MAT 400 taught by Professor Jamespotvein during the Fall '08 term at University of Toronto- Toronto.

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08-Biometrics-Lecture8-Day2-Part2-16-00-17-30 - Continuing...

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