Registry

Module Specifications

Current Academic Year 2012 - 2013
Please note that this information is subject to change.

Module Title	Biometrics
Module Code	CA641A
School	School of Computing
Online Module Resources
Module Co-ordinator	Semester 1: Alistair Sutherland Semester 2: Alistair Sutherland Autumn: Alistair Sutherland
Module Teacher	Alistair Sutherland
NFQ level	8	Credit Rating	7.5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Description

This module aims to examine modern approaches to automatically identifying or verifying an individual based on one or more biometric traits, e.g. speech, DNA, fingerprints. It will cover all or most aspects of a biometric recognition from data acquisition through signal processing to pattern recognition. Students taking this model will already be able to program, have solid mathematical competence, and will have an interest in any or all of: biometrics, pattern recognition, signal processing.

Learning Outcomes

1. Explain the operations and distinguishing features of elements of a biometric recognition system
2. Describe the primary techniques and technologies used in the common biometrics, e.g. speech, DNA, fingerprints
3. Use mathematics appropriate to biometric processing
4. Process novel data in algorithms used in biometric recognition systems
5. Evaluate the appropriateness of different biometric recognition technologies
6. Design and implement a biometric recognition system
7. Communicate experimental and design work in formal writing while citing the work of others which has contributed to the student's work

Workload	Full-time hours per semester
*Type*	*Hours*	*Description*
Lecture	36	Face-to-face and online screencasts
Laboratory	24	Assignment or set exercises
Moodle discussion	6	Queries, Replies, Monitoring
Assignment	40	Individual Projects
Independent learning	81	At individual's discretion
Total Workload: 187

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Generic mathematical techniques:.
Review of probability, statistics, linear algebra..

Usage issues of biometric systems:.
Benefits and risks; Costs; Privacy..

System architecture:.
Data acquisition; Signal processing; Feature extraction; Enrollment - model/template creation; Recognition/Acceptance decisions..

Digital signal processing:.
Time and space frequency-domain analysis; Feature extraction and preprocessing; Principal Component Analysis..

Pattern Recognition:.
Probabilistic models and distance-based templates and metrics; Accuracy, false acceptance rates, false rejection rates; Various algorithms relating to - Dynamic Programming, Gaussian classifiers, Hidden Markov Models, Support Vector Machines, Sequence matching..

Overview of the primary biometrics:.
Speech; Fingerprint; Face; Iris, DNA..

Other:.
Signatures and key-strokes; Multifactor identification.

Assessment Breakdown
Continuous Assessment	30%	Examination Weight	70%

Course Work Breakdown
Type	Description	% of total	Assessment Date
In Class Test	Assessment of Infrastructural Mathematics	10%	Week 4
Practical/skills evaluation	Planning, design, implemntation and evaluation of a basic biometric recognition system; Formal write-up; Review	10%	Week 8
Other	MATLAB-based exercises	5%	Week 10
Other	DNA-related assessed exercises	5%	Week 12

Reassessment Requirement
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 3

Indicative Reading List

Other Resources

None

Array

Programme or List of Programmes

MSSF

MSc in Security & Forensic Computing

Timetable this semester: Timetable for CA641A

Date of Last Revision

25-AUG-11

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