Aiming at the problem that the method based on self quotient image ignores the selection of features

a novel face recognition approach based on self quotient image and random projection is proposed. Firstly

the self quotient image method is used for preprocessing face image in order to remove the effect of illumination. Secondly

constructs an initial sample space using linear discriminat analysis. Furthermore

samples are projected to different subspaces by iterative random projection and extracts more completeness and discriminative of the illumination invariant feature. Finally

the nearest neighbor classifier is used to classify sample. Experiments on Yale B and AR face database show that the proposed method can extract face features which are robust to illumination and discriminative

and improve the accuracy of face recognition under illumination change.