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Higher Education Technical Challenges Hub: Module Specification

ICT34M3 Biometric techniques II

pdf version of module specification

Download the module specification

pdf version of module specification


Module:

Programme:

ICT

ECTS:

6

Type:

Masters

Module name:

Biometric techniques II


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 build a biometric system regardless the technology used. This module builds on ICT18M2 (Bio-metric techniques I) and complements the module ICT33M1 (Bio-metrics identification systems and video surveillance). 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):
* Physiological traits and the methods of recognition. Fingerprints and the used techniques — optical, ultrasonic, thermal and capacitance. Facial recognition (2D and 3D methods). Hand geometry and palm print. Hand vein pattern recognition. Iris recognition. Retina recognition.
* Behavioral traits and the methods of recognition. Dynamic signature recognition. Voice recognition.
* Operation of a biometric system. Sensor, feature extraction, matching and decision-making, system data base modules; verification and identification modes of an operation system.

2. Implementing a bio-metric system:
* The structure of a bio-metric system.
* International Biometrics Standards: ISO (the International Organization for Standardization) and IEC (the International Electrotechnical Commission).
* Programming languages and techniques for bio-metrics.
* 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 such as:

* Design of a facial recognition software program using an image file as a source.
* Design of an object recognition software program (e.g, a hand with finger positions) using an image file as a source.
* Design of a software program to follow an object in motion using a sequence of image files as a source.

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


Learning outcomes:

Knowledge

Skills

Competences

Bio-metric and verification system design and operation.

Analyze bio-metric systems in engineering disciplines.

In developing any part involved in a bio-metric system: Measure, comparison, decision-making.

Physiological and behavioral characteristics to use as metrics.

Design, test and deploy systems containing hardware and software components.

Apply artificial intelligence and pattern recognition algorithms.

Security risks. Authentication levels. Ethical implications.

Mathematical signal/image encoding and enhancement.


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