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NOVEL FACIAL IMAGE RECOGNITION TECHNIQUES EMPLOYING PRINCIPAL COMPONENT ANALYSIS
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TitleNOVEL FACIAL IMAGE RECOGNITION TECHNIQUES EMPLOYING PRINCIPAL COMPONENT ANALYSIS
AuthorABDELWAHAB, MOATAZ MAHMOUD
KeywordsTransform Domain 2DPCA
AbstractRecently, pattern recognition/classification has received considerable attention in diverse engineering fields such as biomedical imaging, speaker identification, fingerprint recognition, and face recognition, etc. This study contributes novel techniques for facial image recognition based on the Two dimensional principal component analysis in the transform domain. These algorithms reduce the storage requirements by an order of magnitude and the computational complexity by a factor of 2 while maintaining the excellent recognition accuracy of the recently reported methods. The proposed recognition systems employ different structures, multicriteria and multitransform. In addition, principal component analysis in the transform domain in conjunction with vector quantization is developed which result in further improvement in the recognition accuracy and dimensionality reduction. Experimental results confirm the excellent properties of the proposed algorithms.
AdviserMikhael, Wasfy
PublisherUniversity of Central Florida
DegreePh.D.
Degree DisciplineSchool of Electrical Engineering and Computer Science
Degree GrantorEngineering and Computer Science
Degree ProgramElectrical Engineering PhD
Graduation Date2007-12-01
TypeDoctoral dissertation
Access LevelCampus - Allow Only UCF Community Access
RepositoryUniversity Archives
Repository CollectionElectronic Theses and Dissertations
IdentifierCFE0001977
Access Linkhttp://purl.fcla.edu/fcla/etd/CFE0001977

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