Implementation and Evaluation of Face Recognition Based Identification System

  • Faruk Can Elbizim Istanbul Commerce University
  • Mustafa Cem Kasapbasi Istanbul Commerce University
Keywords: Face Recognition, EigenFaces, FisherFace, LBPHFace, SURF


Face recognition has been widely used and implemented to many systems for the purpose of authentication, identification, finding faces, etc. In this study Yale face database [1] is used which consist of 15 different people. For each of person there are 11 different images with different face expressions. In this study images are categorized as normal, normal and center light, normal and happy, normal with left light and right light. In order to recognize these faces 4 different face recognition methods namely Eigenface, Fisherface, LBPHface and SURF are utilized in the developed environment. In order to test the mentioned face recognition algorithms a software is developed using EmguCV in .NET environment. After evaluating and comparing the obtained confusion matrix amongst other the LBPHface  method was found to be superior method with an average accuracy of 99%, it was ~98% SURF, ~97% for EigenFace and FisherFace. FicherFace was slightly better then the Eigenface method.


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Author Biography

Mustafa Cem Kasapbasi, Istanbul Commerce University
Image Procesıng, face Recognıtıon, Steganographyö Cryptography


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How to Cite
F. Elbizim and M. Kasapbasi, “Implementation and Evaluation of Face Recognition Based Identification System”, IJISAE, pp. 17-20, Jul. 2017.
Research Article