A Simulated Annealing and 2DPCA Based Method for Face Recognition

Abstract

In this paper we address the problem of face recognition based on two-dimensional principal component analysis (2DPCA). The similarity measure plays an important role in pattern recognition. However, with reference to the 2DPCA based method for face recognition, studies on similarity measures are quite few. We propose a new method to identify the similarity measure by simulated annealing (SA), which is called SA similarity measure. Experimental results on two famous face databases show that the proposed method outperforms the state of the art methods in terms of recognition accuracy.