This instructor is available by email at email@example.com, by telephone (962-4261), and during office hours (CI 2042). Office hours are posted on the instructor’s home page and located on the door to his office. In addition, students can arrange to meet with the professor outside of normal office hours by contacting him via email or phone or schedule using Outlook.
You are expected to
take an active role in your learning in this course. This includes regular
attendance, in class participation and discourse, reading the textbook and
prescribed articles and handouts, and completing all course requirements. You
are encouraged to continue discourse outside of the class with student peers
and the instructor.
Prerequisites: Statistics 215, Discrete Structures and a high-level programming course, i.e. Java, C-, C++, Python, etc. Consideration can and will be made for special circumstances, e.g. students who may not have the prerequisites.
Textbook: To be announced in class.
• N. K. Ratha and V. Govindaraju, Advances in Biometrics: Sensors, Algorithms and Systems, Springer, 2008
• D. Maltoni, D. Maio, A. K. Jain, and S. Prabhakar, Handbook of Fingerprint Recognition, Springer Verlag, 2003.
• A. K. Jain, R. Bolle, S. Pankanti (Eds.), BIOMETRICS: Personal Identification in Networked Society, Kluwer Academic Publishers, 1999.
• J. Wayman, A.K. Jain, D. Maltoni, and D. Maio (Eds.), Biometric Systems: Technology, Design and Performance Evaluation, Springer, 2004.
• In addition, a number of journals, including Pattern Recognition, Pattern Recognition Letters, IEEE Trans. Pattern Analysis & Machine Intelligence (PAMI), IEEE Trans. Image Processing, IEEE Trans. Speech and Audio Processing and IEEE Security & Privacy Magazine routinely publish papers on biometrics.
Introduction: Automatic and reliable identification of individuals for issuing official documents (e.g., passport and visa) and providing access to secure facilities (e.g., military base) and proprietary information (e.g., corporate websites) has become an essential part of our modern networked society. Biometric recognition systems utilize the physiological or behavioral characteristics of an individual for identification. By using biometrics, it is possible to establish an identity based on "who you are", rather than by "what you possess" (e.g., an ID card) or "what you remember" (e.g., a password). The events of 9/11 have generated huge interest in the design, deployment and evaluation of biometric systems. In this course we will study the design of various biometric systems based on fingerprints, voice, face, hand geometry, palmprint, iris, retina, and other modalities. Multimodal biometric systems that use two or more of the above characteristics will be discussed. Biometric system performance and issues related to the security and privacy aspects of these systems will also be addressed.
Participation: Regular class attendance is required. Student will not be allowed to makeup assignments, exams, or projects.
The cumulative score will be mapped to the course grade as follows: 90% or higher: 4.0; 85% to 90%: 3.5; 80% to 85%: 3.0 and so on.
The midterm exam will test the understanding of basic biometric system concepts, such as false accept rate (FAR), fusion rules, template protection, fingerprint features, etc.
The students will work in teams of two on a particular deployment of biometric systems. Some suggested applications are:
• Biometrics in Transportation (Airports, Railroads, etc)
• Biometrics in Commercial Applications (Grocery Stores, Hotels, etc)
• Biometrics in Medical Services (Healthcare, Document Security, etc)
• Biometrics in Forensics (Criminal Justice, Disaster Victim Identification)
• Biometrics and Smart Cards (Federal Identify Cards, National ID, etc)
a. http://www.smartcardalliance.org/pdf/industry_info/smartcardhandbook.pdf (United States)
b. http://www.gemplus.com/pss/id_security/download/Oman_case_study_Aug04.pdf (Oman)
c. http://www.identitycards.gov.uk (united kingdom)
d. http://www.asean-ssa.org/sssidsyssssphils.pdf (Philippines)
• Biometrics in Department of Defense
• Standardization of Biometric Systems
• Students will make a presentation of the case study to the class in the middle of the semester.
The students will work in teams of 2 on a class project. Possible topics for the project are:
• Image quality assessment
• Template characteristics with regard to the change over time
• Performance comparisons between human and computer systems
• Performance comparisons among different biometric sensors and modalities
Students will submit a project report at the end of the semester and will present their project results to the class. The class will evaluate each teams project and provide a peer score for the each team. The peer score will be combined with the instructor’s evaluation of the project to achieve the final grade for the project.
If you have a disability and need reasonable accommodation in this course, you should inform the instructor of this fact in writing within the first week of class or as soon as possible. If you have not already done so, you must register with the Office of Disability Services in Westside Hall (extension 3746) and obtain a copy of your Accommodation Letter. You should then meet with your instructor to make mutually agreeable arrangements based on the recommendations of the Accommodation Letter.
Students are responsible for submitting their own work. Students who cooperate on oral or written examinations or work without authorization share the responsibility for violation of academic principles, and the students are subject to disciplinary action even when one of the students is not enrolled in the course where the violation occurred.