On the basis of
The course content will be complementary to the course IMT4721 "Authentication".
Expected learning outcomes
After the course, the students should have acquired:
1. Knowledge about common statistical tools for biometrics
2. Insight into advantages and disadvantages of biometric characteristics
3. Understanding of multimodal biometrics
4. Knowledge of ethical and privacy issues in biometrics.
5. Understanding of the threats and protection mechanisms for biometric data
• Fingerprint recognition
• Vein recognition
• Face recognition specifically focused on three dimensional data
• Iris recognition
• Multimodal biometrics
• Attack mechanisms
• Privacy Enhancing Technologies
Teaching Methods (additional text)
Tutorial: Afternoon sessions with seminar discussion and practical tasks
Form(s) of Assessment
Written exam, 3 hours
Form(s) of Assessment (additional text)
Written examination in English
Alphabetical Scale, A(best) – F (fail)
Evaluated by an external examiner.
Ordinary re-sit examnination.
Students can contribute a research report (term paper) on a topic that is chosen by the student in coordination with the lecturer, which will be considered for the assessment
 LI , S . Z. , AND JAIN, A. K. , Eds. Handbook of Face Recognition. Springer-Verlag,
Heidelberg, Germany, 2005.
 MALTONI , D. , MAIO, D. , JAIN, A. K. , AND PRABHAKAR , S . Handbook of Fingerprint Recognition. Springer-Verlag, Heidelberg, Germany, 2005.
 WAYMAN, J . , JAIN, A. , MALTONI , D. , AND MAI O, D. , Biometric Systems.
Springer-Verlag, Heidelberg, Germany, 2004.
 TUYLS, P., SKROIC, B., KEVENAAR, T. Security with Noisy Data. Springer-Verlag, 2007
In case there will be less than 5 students that will apply for the course, it will be at the discretion of Studieprogramansvarlig whether the course will be offered or not an if yes, in which form.