Face recognition using Hidden Markov Models

Ballot, Johan Stephen Simeon (2005-03)

Thesis

This thesis relates to the design, implementation and evaluation of statistical face recognition techniques. In particular, the use of Hidden Markov Models in various forms is investigated as a recognition tool and critically evaluated. Current face recognition techniques are very dependent on issues like background noise, lighting and position of key features (ie. the eyes, lips etc.). Using an approach which specifically uses an embedded Hidden Markov Model along with spectral domain feature extraction techniques, shows that these dependencies may be lessened while high recognition rates are maintained.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/2577
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