10-Biometrics-Lecture-10-Part1-2008-11-24

10-Biometrics-Lectur - 1 Biometrics http/scgwww.epfl.ch/courses Master SC – Information and Communication Security Dr Andrzej Drygajlo Speech

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Unformatted text preview: 1 Biometrics http://scgwww.epfl.ch/courses Master SC – Information and Communication Security 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) 2 Biometrics - Contents • Fundamentals of Biometrics • Analysis, Modeling and Interpretation of Biometric Data • Leading Biometric Technology • Multimodal Biometrics • Biometric Standards • Small, Medium and Large Scale Biometric Systems • Integration of biometrics with other existing technologies • Behavioral Biometrics in Human-Machine Communication • Securing Biometric Data and Systems • Biometric Encryption • Biometric Applications • Privacy and Legal Issues 3 • Speaker Recognition • Dynamic Signature • Fingerprints • Iris • Face • Hand • Others • Multimodal Biometrics Leading Biometric Technology 4 Statistical Modelling – How exceptional is speech? Fingerprint Voice Signature Face Iris Hand 5 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 6 Dorsal surface Visible-light image Thermal image Hand-geometry (shape) Vein patterns (dorsal veins)- biometric features- aliveness features Visible-light and Thermal Images 7 Hand geometry and Hand palm Hand geometry Hand palm 8 Identifiable biometric characteristics • Biological traces – DNA (DeoxyriboNucleic Acid), blood, saliva,etc. • Biological (physiological) characteristics – fingerprints , eye irises and retinas, hand palms, veins and geometry , and facial geometry • Behavioral characteristics – dynamic signature , gait, keystroke dynamics, lip motion • Com bined – voice 9 Palmar Surface Hand shape Fingerprints Palm print Finger strips (digitprints) Palmar veins 10 References (Hand geometry) • 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. 11 Hand Geometry Hand geometry reader by Recognition Systems 12 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 but not cheap setup • Good performance on a medium sized database • A good tradeoff between cost and level of security of the application 13 Pegged v/s Peg-less Systems 14 Pegged v/s Peg-less Systems • Pegged Systems • Pros: • Predefined axis to measure features along...
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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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10-Biometrics-Lectur - 1 Biometrics http/scgwww.epfl.ch/courses Master SC – Information and Communication Security Dr Andrzej Drygajlo Speech

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