Face recognition with single training sample based on fuzzy decision and MSD

To improve the recognition performance of face recognition with single training sample, a face recognition algorithm based on fuzzy decision and maximum scatter difference with single training sample is proposed in this paper. With this method, each training sample is divided into several blocks to increase the number of elements in training sample set, on which the maximum scatter difference algorithm is performed to get the optimal projection matrix. Therefore, the features of training sample and testing facial images could be obtained by projecting them onto optima projection matrix achieved above. During the recognition stage, the fuzzy decision is used to classify. Extensive experiment based on ORL and FERET illustrates the feasibility of the proposed method.