Akademik Veri Yönetim Sistemi
International Journal of Intelligent Systems and Applications in Engineering, cilt.5, sa.Special Issue, ss.17-20, 2017 (Hakemli Dergi)
Face recognition has been widely used and implemented to many systems for the purpose of authentication, identification, findingfaces, etc. In this study Yale face database [1] is used which consist of 15 different people. For each of person there are 11 different imageswith different face expressions. In this study images are categorized as normal, normal and centre light, normal and happy, normal withleft light and right light. In order to recognize these faces 4 different face recognition methods namely Eigenface, Fisherface, LBPHfaceand SURF are utilized in the developed environment. In order to test the mentioned face recognition algorithms a software is developedusing EmguCV in .NET environment. After evaluating and comparing the obtained confusion matrix amongst other the LBPHface methodwas found to be superior method with an average accuracy of 99%, it was ~98% SURF, ~97% for EigenFace and FisherFace. FicherFacewas slightly better then the Eigenface method.