Do singular values contain adequate information for face recognition?

Singular values (SVs) have been usedfor face recognition by many researchers. In this paper, we show that the SVs contain little useful information for face recognition and most important information is encodedin the two orthogonal matrices of the SVD. Experimental results are given to support this observation. To overcome this problem, a new methodfor face recognition basedon the above finding is proposed. The face image is projectedon to the orthogonal basis of SVD and then the vectors of coefficients are usedas the face image features. By using probability density of this image feature obtainedby a simplified EM algorithm, the Bayesian classifier is adopted to recognize the unknown faces. The proposed algorithm obtains acceptable experimental results on the ORL face database.