Comparative study of some face recognition algorithms

In this paper, some of face recognition algorithms are compared, which are based on Two-dimensional principal component analysis (2DPCA), singular value decomposition (SVD) and the fusion of 2DPCA and SVD. The experiment results, by means of ORL and Yale face database, indicate that the algorithm combined 2DPCA and SVD-U has a higher recognition rate, 87% and 95.9%, respectively. And it can have better recognition precision other algorithms mentioned in this paper. Furthermore, the fusion algorithm improves the real-time characteristics in the condition of keeping the recognition precision.