With human society becoming increasingly computerised, the use of biometrics to automatically
establish the identity of an individual is of great interest in a wide variety of
applications. Facial appearance is an appealing biometric, on account of its relatively
non-intrusive nature. As such, automated face recognition systems have been the subject
of much research in recent years.
This dissertation describes the development of a fully automatic face recognition
system, and provides an analysis of its performance under various di erent operating
conditions, in comparison with results published in prior literature. In addition to giving
a detailed description of the mathematical underpinnings of the techniques used by the
system, we discuss the practical considerations involved in implementing the described
techniques.
The system presented here uses the eigenface approach to representing facial features.
A number of di erent recognition techniques have been implemented and evaluated.
These include a number of variants of the original eigenface technique proposed by
Turk and Pentland, as well as a related technique based on the probabilistic approach of
Moghaddam et al.
Due to the wide range of datasets used to evaluate face recognition systems in
the literature, it is di cult to reliably compare the performance of di erent systems. The
system described here has been tested with datasets encompassing a wide range of di erent
conditions, allowing us to draw conclusions about how the characteristics of the test data
a ect the results that are obtained.
The performance of this system is comparable to other eigenface-based systems
documented in the literature, achieving success rates in the region of 85% for large datasets
under controlled conditions. However, performance was observed to degrade signi cantly
when testing with more free-form images; in particular, the e ects of ageing on facial
appearance were noted to cause problems for the system. This suggests that the matter
of ageing is still a fruitful direction for further research. / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2012.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/10444 |
| Date | January 2012 |
| Creators | Vawda, Nadeem. |
| Contributors | Tapamo, Jules-Raymond. |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
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