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Face recognition using Hidden Markov Models

dc.contributor.advisorDu Preez, J. A.en_ZA
dc.contributor.advisorHerbst, B. M.
dc.contributor.authorBallot, Johan Stephen Simeonen_ZA
dc.contributor.otherUniversity of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.
dc.date.accessioned2008-06-30T10:39:25Zen_ZA
dc.date.accessioned2010-06-01T08:52:45Z
dc.date.available2008-06-30T10:39:25Zen_ZA
dc.date.available2010-06-01T08:52:45Z
dc.date.issued2005-03
dc.identifier.urihttp://hdl.handle.net/10019.1/2577
dc.description.abstractThis 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.en_ZA
dc.language.isoenen_ZA
dc.publisherStellenbosch : University of Stellenbosch
dc.subjectTheses -- Electrical and electronic engineeringen_ZA
dc.subjectDissertations -- Electrical and electronic engineeringen_ZA
dc.subject.lcshHuman face recognition (Computer science)en_ZA
dc.subject.lcshPattern recognition systemsen_ZA
dc.subject.lcshMarkov processesen_ZA
dc.subject.otherElectrical and Electronic Engineeringen_ZA
dc.titleFace recognition using Hidden Markov Modelsen_ZA
dc.typeThesisen_ZA
dc.rights.holderUniversity of Stellenbosch


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