DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING

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    Quantitative evaluation of principal component analysis and fisher discriminant analysis techniques in face images.
    (Nigeria Computer Society, 2008) Omidiora, E. O.; Fakolujo, O. A.; Ayeni, R. O.; Olabiyisi, S. O.; Arulogun, O. T.
    "Face recognition is an attractive field in enhancing both the security and the image retrieval activities in the multimedia world. Its natural basis in verification or identification purposes is a major factor of its wide acceptance in this evolving world of information technology. In this paper, experiments based on black African faces using Principal Component Analysis (OPCA) and Fisher Discriminant Analysis (OFDA) techniques were carried out. The design of the face recognition system was separated into three major sections - image acquisition and standardisation, dimensionality reduction, training and testing for recognition. Under static mode, experiments were performed on single scaled images without rotation, OPCA and OFDA both give recognition accuracies of between 89% and 97%;and) 88% and 98% respectively. These have been achieved at different levels of cropping. Despite the constraint created by the resources available, different results got showed that standard face recognition system could be developed using both algorithms. "
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    A survey of face recognition techniques
    (Faculty of Technology, University of Ibadan, 2007) Omidiora, E. O.; Fakolujo, O. A.; Ayeni, R. O.; Ajila, T. M.
    A review of face recognition techniques has been carried out.Face recongition has been an attractive field in the society of both biological and computer vision of research. It exhibits the characteristics of being natural and low-intrusive. In this paper, an updated survey of techniques for face recognition is made. Methods of face regonition , such as geometric, statistical and neural networks approaches are presented and analyzed. The comparative performance of the variaous approaches is discussed.