Performance analysis of face recognition algorithms

The usage areas of biometric systems are becoming widespread in today's technology. Face recognition systems among biometric systems; Ease of use, reliability, cost, etc., the preference between public institutions, commercial enterprises and researchers is increasing. In this study, it is suggested that students should use face recognition system instead of traditional methods of absenteeism in education and training institutions. It is very important that face recognition systems work quickly with matching people correctly. In this study, the training and recognition times of Eigenfaces, Fisherfaces and Local Binary Pattern algorithms used in face recognition systems are calculated by using Visual C ++ and Python programming languages using ORL dataset.