The singular value vector of face image is analyzed and its nature is revealed

i.e.

the singular values of face image are obtained by decomposing the face in the special basis space that is determined by the face image.Based on this result

the intrinsic reasons that singular value vector-based recognition methods have the low recognition accauracy are follows: singular value vectors of arbitrary two face images have not the equivalent basis space in general;there is no one-to-one correspondence between singular value vector and face image;singular value vectors are not separated.Finally

a novel face recognition method coined class estimated basis space method is presented.ORL

ORL-NWPU1 and ORL-NWPU2 database are used to test

and the experimental results show the correctness of analysis and the proposed method.