Human face recognition based on radial basis probabilistic neural network

In this paper, a novel human face recognition method based on radial basis probabilistic neural network (RBPNN) is proposed. The orthogonal least square algorithm (OLSA) is used to train the RBPNN and the recursive OLSA is adopted to optimize the structure of the RBPNN. The Olivetti Research Laboratory (ORL) facial database, which is preprocessed by wavelet transformation, is used to test the proposed approach. The experimental results show that the RBPNN achieves higher recognition rate and better classification efficiency with respect to radial basis function neural network (RBFNN) and BP neural network.