1. Biometrics Austen Hayes and Cody Powell

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

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

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

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

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

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

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

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

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

11. 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

12. Other Types  Keystroke  Gait  DNA  Odor

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

14. Government Applications  Passport control  Border control  Access Control

15. Forensic Applications  Missing Persons  Corpse identification  Criminal investigations

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

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

18. Constraints on Biometrics  “Unconstrained” Image

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

20. Biometrics Research at Clemson  Aging Research

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

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

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

24. Conclusion  Questions?

25. Sources  Biometrics.gov. Web. 05 Dec. 2011. http://www.biometrics.gov/ReferenceRoom/Introduction.aspx http://www.biometrics.gov/ReferenceRoom/Introduction.aspx  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): 4-20. IEEE Xplore. Web. 5 Dec. 2011. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1262027 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1262027  Jain, Anil K., Patrick J. Flinn, and Arun A. Ross. Handbook of Biometrics. New York: Springer. Web. 5 Dec. 2011. http://libcat.clemson.edu/record=b2478857 http://libcat.clemson.edu/record=b2478857  Phillips, Jonathon P., Alvin Martin, C. L. Wilson, and Mark Przybocki. "An Introduction Evaluating Biometric Systems." Computer 33.2 (2000): 56-63. IEEE Xplore. Web. 5 Dec. 2011. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=820040 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=820040  http://bprl.cs.clemson.edu/about.html http://bprl.cs.clemson.edu/about.html  http://bprl.cs.clemson.edu/projects.html http://bprl.cs.clemson.edu/projects.html