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Higher Education Technical Challenges Hub: Module Specification

ICT33M3 Biometrics identification systems and video surveillance

pdf version of module specification

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pdf version of module specification








Module name:

Biometrics identificaton systems and video surveillance

Scope and form:

Duration (weeks; Hours/week):

15 weeks, 4h/week

Type of assessment:

Individual laboratory work and end of semester examination.

Qualified Prerequisites:

ICT18M2 (Bio-metric techniques I).

General module objectives:

The objective of this module is to provide the students with sufficient knowledge to with sufficient knowledge to extract biometric signatures based on images or video. This module builds on ICT18M2 (Bio-metric techniques I) and complements the module ICT34M1 (Bio-metric techniques II). In this module, the theory and techniques introduced in ICT18M2 (Bio-metric techniques I) are further developed and practical work is undertaken to practice information extraction from biometric data.

Topics and short description:

The module is divided into three parts. The first part is a review of the key material previously studied and will be used as the basis for the advanced material and laboratory practical work:

1. Review of key material studied in ICT18M2 (Bio-metric techniques I):
* Operation of a biometric system. Sensor, feature extraction, matching and decision-making, system data base modules; verification and identification modes of an operation system.
* Multibiometrics. Using several sources of biometric data. Types of multibiometric systems –multi-sensor, multi-algorithms, multi-instance, multi-sample, multimodal and hybrid.
* Application of biometric systems. The main fields and examples of biometric technics application.

2. Implementing a bio-metric system:
* Biometric and verification systems overview.
* Non-contact perception and non-conventional imaging: Different types of non-conventional acquisition systems that yield to biometric information are covered.
* Image-based challenges to infer biometric information.
* Analysis of the effectiveness of a bio-metric system.
* Image and video files:  image quality and file formats. Image encoding and enhancement.
* Machine learning (supervised and unsupervised learning).
* Algorithms for pattern recognition for bio-metric data including palm print pattern recognition, vein pattern analysis, finger print pattern recognition, gait/pose recognition and facial thermography.
* Privacy and security issues: Information collection, storage, use and dissemination. Human issues and vulnerability. Ethics.

3. Laboratory practical exercises.
The laboratory work will involve the writing of software code in a suitable programming language (e.g., Java) in order to perform bio-metric identification. Each exercise will require the work undertaken to be written up as a laboratory report and the operation of the developed software code is to be suitably presented.  The laboratories will be undertaken to write software programs to undertake specific functions on image and video files.

The module assessment is based on the following:
* The exercises undertaken in the laboratories.
* An end of semester examination.

Learning outcomes:




Biometric and verification system.

Analyze biometric systems in engineering disciplines.

In assessing the need for video surveillance technology to infer biometric information.

Image-based challenges.

Identify possible security breaches from image acquisition and manipulation system.

Robust biometric inference from images.

Pattern recognition for bio-metric data.

Mathematical signal/image encoding and enhancement.

Security risks. Authentication levels. Ethical implications.

Recommended literature:

Jain, Anil K., Patrick Flynn, and Arun A. Ross. Handbook of biometrics. Springer Science & Business Media, 2007.
Vacca, John R. Biometric technologies and verification systems. Butterworth-Heinemann, 2007.
N. V. Boulgorius, Konstantinos N. Plataniotis, Biometrics: Theory, Methods and Applications (IEEE Press Sweries on Computational Intelligence), Wiley-IEEE Press, 2009, ISBN 0470247827.
A. K. Jain, A. Ross and S. Prabhakar. “An introduction to biometric recognition,” IEEE Trans. Circuits Syst. Video Technology, Special Issue Image- and Video-Based Biomet, vol. 14, Issue 1, (2004), pp. 4–20.
A.K. Jain, P.J. Flynn and A. Ross (eds.) (2007) Handbook of Biometrics, Springer.
A. K. Jain, A. A. Ross, and K. Nandakumar. Introduction to biometrics. Springer Science & Business Media, 2011