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The course content will be complementary to the course IMT4721 "Authentication". IMT4611 "Data Analysis and Statistics" is recommended as an accompanying module for this course; although some concepts of applied statistics and decision theory are revisited in this course, students will benefit from the more rigorous treatment of the subject matter in IMT4611.

Forventet læringsutbytte

After the course, the students should acquire:

1. Knowledge about common statistical tools for biometrics

2. Insight into advantages and disadvantages of use of selected types of biometrics

3. Understanding of multimodal biometrics

4. Knowledge of ethical and privacy issues in biometrics.

5. Understanding of protection mechanisms for biometric data

Emnets temaer

1. Fingerprint recognition

2. Iris recognition

3. Face recognition specifically focused on three dimensional data

4. Multimodal biometrics

5. Attack mechanisms

6. Privacy Enhancing Technologies

Pedagogiske metoder

Forelesninger
Oppgaveløsning

Vurderingsformer

Skriftlig eksamen, 3 timer

Karakterskala

Bokstavkarakterer, A (best) - F (ikke bestått)

Sensorordning

Evaluated by the lecturer.

Gjennomføring av kontinuasjon

The whole course must be repeated.

Tillatte hjelpemidler (gjelder kun skriftlig eksamen)

Approved calculator

Obligatoriske arbeidskrav

None.

Læremidler

[1] LI , S . Z. , AND JAIN, A. K. , Eds. Handbook of Face Recognition. Springer-Verlag,

Heidelberg, Germany, 2005.

[2] MALTONI , D. , MAIO, D. , JAIN, A. K. , AND PRABHAKAR , S . Handbook of Fingerprint Recognition. Springer-Verlag, Heidelberg, Germany, 2005.

[3] WAYMAN, J . , JAIN, A. , MALTONI , D. , AND MAI O, D. , Biometric Systems.

Springer-Verlag, Heidelberg, Germany, 2004.

[4] JAIN, L.C. , HALICI, U. , HAYASHI, I. ; LEE, S.B., TSUTSUI, S. Intelligent Biometric Techniques in Fingerprint and Face Recognition. CRC PressVerlag, 1999.

[5] TUYLS, P., SKROIC, B., KEVENAAR, T. Security with Noisy Data. Springer-Verlag, 2007