Face Recognition Based on PCA and 2DPCA with Single Image Sample

Abstract

For most of the face recognition techniques will suffer serious performance drop when there is only one training sample per person, a face recognition method based on principle component analysis and two dimension principle component analysis is proposed. We compared our methods with PCA and 2DPCA. In the experiments, the nearest neighbor classifier is used to recognize different faces from the ORL and Yale face database. Experimental results show that the proposed method improved the recognition performance effectively in comparison with other method.