Please use this identifier to cite or link to this item: http://ir.library.ui.edu.ng/handle/123456789/2153
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dc.contributor.authorOmidiora, E. O.-
dc.contributor.authorFakolujo, O. A.-
dc.contributor.authorAyeni, R. O.-
dc.contributor.authorAdeyanju, I. A.-
dc.date.accessioned2018-10-12T08:43:19Z-
dc.date.available2018-10-12T08:43:19Z-
dc.date.issued2008-
dc.identifier.issn1816-949X-
dc.identifier.otherJournal of Engineering and Applied Science 3(7), pp. 524-531-
dc.identifier.otherui_art_omidiora_optimised_2008-
dc.identifier.urihttp://ir.library.ui.edu.ng/handle/123456789/2153-
dc.description.abstractA face recognition system is one of the most desirable biometric identification such as computerized access control, document control and database retrieval. Although, several researches have been done on face recognition, most (if not all) have made use of non-black faces or very few numbers of black faces in their experiments. This study presents results of experiments based on black African faces (with and without tribal marks) using the optimized Fisher Discriminant Analysis. In the experiment, different sizes of gray scale images were used for recognition performance accuracy of between 88 and 99% were obtained. Also, taking into consideration was the rate of identifying an image using the same number of images to test the face recognition system. While, a completely robust real-time face recognition system is still under heavy investigation and development, the implemented system serves as an extendable foundation for future research.en_US
dc.language.isoen_USen_US
dc.publisherMedwell Journalsen_US
dc.subjectface,en_US
dc.subjectoptimized fisher discriminant analysisen_US
dc.titleOptimised fisher discriminant analysis for recongnition of faces having black features.en_US
dc.typeArticleen_US
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