Face Recognition Based on Log-Gabor and Orthogonal IsoProjection

In view of the problems of feature extraction in face recognition,a Log-Gabor and orthogonal supervised IsoProjection based algorithm for face recognition was proposed in this paper.The proposed algorithm first gets the high-order nonlinear statistical information by calculating the Log-Gabor wavelet representation of face images.Then the orthogonal constrained conditions added to the original optimal problem and the iterative formulae for finding a set of orthogonal optimal projection vectors are deduced.The orthogonal basis can help to preserve the information of nonlinear sub-manifold space which is related to distance and reconstruct data.The experimental results on ORL and PIE face database illustrate the effectiveness of the proposed method.