Human Face Recognition Using Radial Basis Function Neural Network

A neural network based face recognition system is presented in this paper. The system consists of two main procedures. The first one is face features extraction using Pseudo Zernike Moments (PZM) and the second one is face classification using Radial Basis Function (RBF) neural network. In this paper, some new results on face recognition are presented. Simulation results indicate that PZM with RBF neural network produce higher detection and lower missing rates than several existing state-of-theart face detection systems, with an average false detection rate. Also experimental results show that high order degrees of PZM contain very useful information about face recognition process. The proposed system has been applied on face database of Olivetti Research Laboratory (ORL) with very good results.