course-details-portlet

IMT6071 - Biometrics

About

Examination arrangement

Examination arrangement: Assignment
Grade: Passed/Failed

Evaluation form Weighting Duration Examination aids Grade deviation
Assignment 100/100

Course content

-Fingerprint recognition
-Vein recognition
-Face recognition specifically focused on three dimensional data
-Iris recognition
-Multimodal biometrics
-Score Normalization
-Attack mechanisms
-Privacy Enhancing Technologies
-Revocable biometric references

Learning outcome

Knowledge

The candidate possesses knowledge at the most advanced frontier in the field of biometrics.

The candidate has mastered academic theory and scientific methods in biometrics.

The candidate is capable of considering suitability and use of different methods and processes in research in the field of biometrics.

The candidate is capable of contributing to development of new knowledge, theories, methods, interpretations and forms of documentation in biometrics.

Skills

The candidate is capable of formulating problems, planning and completing research projects in biometrics.

The candidate is capable of doing research and development at a high international level.

The candidate is capable of handling complex academic tasks.

The candidate can challenge established knowledge and practice in biometrics. More specifically after the course, the candidate should have the following capabilities:

developed a systematic understanding of biometric systems and their capabilities

mastered multiple modality-specific feature extraction and have the ability to evaluate their suitability for given acquisition characteristics

developed in-depth insights into statistical methods and tools for biometrics and their performance evaluation

the ability to synthesize multi-modal analysis methods and solve score normalisation problems in fusion systems

the ability to appraise and differentiate threats to biometric reference data, judging and realizing adequate protection mechanisms accordingly

the ability to perform in-depth assessment of biometric component placement within a security system

demonstrated the ability to design and defend a biometric security system when provided with a threat scenario

General competence

The candidate is capable of identifying relevant - and possibly new - ethical problems and exercising research in biometrics with academic integrity.

The candidate is capable of managing complex interdisciplinary tasks and projects.

The candidate is capable of disseminating the results of research and development in biometrics through approved national and international publication channels.

The candidate is capable of taking part in debates in international forums within the field of biometrics.

The candidate is capable of considering the need for, taking initiative to and engaging in innovation in the field of biometrics. More specifically the candidate will have the competence to

demonstrate the ability to design a biometric system suitable for a given scenario

judge the relevance of ethical and privacy issues

investigate for a given scenario technical solutions and evaluate them in a critical analysis.

synthesize new ideas during evaluation phase

communicate with peers in the biometric community in terms of reviewing research topics

manage team work

Learning methods and activities

-Lectures
-Assignments
-Seminar(s)

Additional information: Seminar with term paper presentation

Compulsory requirements: None

Further on evaluation

Utfyllende om kontinuasjon:

 The whole course must be repeated.

Vurderingsformer:

Candidates must provide a research report (term paper) on a topic that is chosen by the candidate in coordination with the lecturer. The term paper should preferably not focus on a survey of methods but rather address original research and be submitted to a scientific conference (e.g. NISK, BIOSIG)

Specific conditions

Admission to a programme of study is required:
Computer Science (PHD-CS)
Information Security (PHD-IS)
Information Security and Communication (PHISCT)

Required previous knowledge

None - however the course content will be complementary to the course "Behavioural Biometrics". The course Machine Learning is recommended as an accompanying module for this course; although some concepts of applied statistics and decision theory are revisited in this course, candidates will benefit from the more rigorous treatment of the subject matter in IMT4612 and IMT 4632.

Course materials

[1] LI , S . Z. , AND JAIN, A. K. , Eds. Handbook of Face Recognition. Springer, 2011.[2] MALTONI , D. , MAIO, D. , JAIN, A. K. , AND PRABHAKAR , S . Handbook of Fingerprint Recognition. Springer, 2009.[3] WAYMAN, J . , JAIN, A. , MALTONI , D. , AND MAI O, D. , Biometric Systems. Springer, 2005.[4] JAIN, L.C. , HALICI, U. , HAYASHI, I. ; LEE, S.B., TSUTSUI, S. Intelligent Biometric Techniques in Fingerprint and Face Recognition. CRC Press, 1999.[5] TUYLS, P., SKROIC, B., KEVENAAR, T.  Security with Noisy Data. Springer, 2007

More on the course

No

Facts

Version: 1
Credits:  5.0 SP
Study level: Doctoral degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2021

Language of instruction: English

Location: Gjøvik

Subject area(s)
  • Informatics
Contact information
Course coordinator:

Department with academic responsibility
Department of Information Security and Communication Technology

Phone:

Examination

Examination arrangement: Assignment

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Spring ORD Assignment 100/100
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

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