CS778-Biometrics (3)

Class Information

001   13222  T (“Tuesday”)   7:20 p.m. - 10:00 p.m.  STI 120

Office Hours

Tuesday   6:15 – 7:00 PM or by appointment (SITE II - Rm. 461)


1.    A. K. Jain, P. Flynn, and A. A. Ross (Eds.), Handbook of Biometrics, Springer, 2008.

2.    H. Wechsler, Reliable Face Recognition Methods, Springer, 2007.


1. R. M. Bolle, J. H. Connell, S. Pankanti, N. K. Ratha, and A. W. Senior, Guide to Biometrics, Springer 2004.

Course Description

Basic principles  and methods for automatic authentication of   individuals.  Biometric modalities include among others face, fingerprints, gait, iris, and speech. Additional topics cover multimodal biometric and data fusion, performance evaluation, and security / integrity and privacy / anonymity.  Course provides the required background in image/ signal processing and  computer   vision,  machine learning and pattern recognition, and neurosciences. Applications include identification, verification, and surveillance. Term project required.






     Biometrics,  the science of recovering or verifying a person's identity, measures the physical or behavioral characteristics that make people unique—including fingerprints, an eye's retina or iris, face, hand geometry, signature and voice—and uses those measurements for personal authentication. Biometrics is related to the science of forensics, which uses and interprets physical evidence for legal purposes.  The importance of biometrics lies in the fact that traditional means of identification and verification are often unreliable or cumbersome: Passwords are difficult to remember and easy to steal. Keys, driver's licenses, and passports can be lost or forged. The human body and its behavior, on the other hand, can't be forgotten, stolen, forged, or misplaced. Practical uses for biometrics are wide spread and include maintaining the security for both physical and cyber space. In particular, biometrics aids in controlling access to an office, computer network or an ATM, smart cards, wireless communication; confirming the identity of buyers and sellers to make electronic commerce safe and reliable; confirming student identity for distant learning; and safeguarding electronic records related to health care services.  



Homework à 10 %

Midterm à Thursday, March 18 à 20 %

[spring break ~ week of March 10]

(Team) Term  Project à  April 22 and April 29  à 40 %

Final à Thursday, May 13 à 30 %

    Follow – up


      Graduate Certificate in Biometrics


     CS 775 / IT 844 – Advanced Pattern Recognition – 2008 - 2009


     Doctoral Dissertation