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Face recognition using Hidden Markov Models

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 is...

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Main Author: Ballot, Johan Stephen Simeon
Other Authors: Du Preez, J. A.
Format: Thesis
Language:English
Published: Stellenbosch : University of Stellenbosch 2008
Subjects:
Theses > Electrical and electronic engineering
Dissertations > Electrical and electronic engineering
Human face recognition (Computer science)
Pattern recognition systems
Markov processes
Electrical and Electronic Engineering
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Summary: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.

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