Biometrics Austen Hayes and Cody Powell

Overview  What is Biometrics?  Types of Biometric Recognition  Applications of Biometric Systems  Types of Authentication  Constraints on Biometrics  Biometric Research at Clemson

What is Biometrics?  Automated method for recognizing individuals based on measurable biological and behavioral characteristics

Finger Print Recognition  Minutiae  Pattern Matching  Problems: sometimes unusable

Vascular Pattern Matching  LED infrared light  Fingers and back of hand  Not completely viable

Iris Recognition  Uses infrared light  Converts Images to vectors  Needs further development

Facial Recognition  Location and position of facial features  Dependent on background and lighting conditions

Voice Verification  Factors: pitch, intensity, quality and duration  Text dependent  Text independent  Problems: include background noise

Hand Geometry  Scan both sides of hand  Primarily used for verification  Not as accurate as other methods

Dynamic Signature  Factors: velocity, acceleration and speed  Mainly used for verification  Problems: forgers could reproduce

Retina Recognition  One of the most secure means of biometrics  Unique to each person  Unique to each eye  Problems: require effort on the part of subjects

Other Types  Keystroke  Gait  DNA  Odor

Commercial Applications  Computer login  Electronic Payment  ATMs  Record Protection

Government Applications  Passport control  Border control  Access Control

Forensic Applications  Missing Persons  Corpse identification  Criminal investigations

Type of Authentication  Authentication  1:1  Verification  1:N

Constraints on Biometrics  Typical “Constrained” Image  Constraints:  Lighting  Distance  Pose  Expression  Time Lapse  Occlusion

Constraints on Biometrics  “Unconstrained” Image

Biometrics Research at Clemson  Biometric and Pattern Recognition Lab  Goals: 1. Usable Biometrics 2. Unconstrained Biometrics

Biometrics Research at Clemson  Aging Research

Biometrics Research at Clemson  Demographics  Older vs. Younger  Males vs. Females  Geographic origin of algorithms

Biometrics Research at Clemson  Periocular Region Recognition  Texture, color, eye shape  Overcome facial occlusion

Biometrics Research at Clemson  Ear Recognition  Not affected by aging or expression  Covert collection of images  Little research performed

Conclusion  Questions?

Sources  Biometrics.gov. Web. 05 Dec  Jain, Anil K., Arun Ross, and Salil Prabhakar. "An Introduction to Biometric Recognition." IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 14.1 (2004): IEEE Xplore. Web. 5 Dec  Jain, Anil K., Patrick J. Flinn, and Arun A. Ross. Handbook of Biometrics. New York: Springer. Web. 5 Dec  Phillips, Jonathon P., Alvin Martin, C. L. Wilson, and Mark Przybocki. "An Introduction Evaluating Biometric Systems." Computer 33.2 (2000): IEEE Xplore. Web. 5 Dec  