Comparison of three face recognition algorithms

Face recognition has received a lot of attention in biometrics and computer vision. A lot of face recognition algorithms have been developed during the past decades. This paper reviews three classical methods Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Elastic Bunch Graph Matching (EBGM). Three algorithms are implemented with Matlab. The algorithm performance is evaluated on three different databases. Scenarios and performance benchmarking are compared for each of the algorithms in terms of recognition accuracy, computational cost, and recognition tolerance.