Multi-resolution elongated CS-LDP with Gabor feature for face recognition

Centre-symmetric local derivative pattern (CS-LDP) algorithm is proposed to describe the local second-order derivative feature of texture. However, CS-LDP can only describe second-order derivative feature of texture on four directions and lost some discriminant information on other directions. Addressing such problems, this paper proposed multi-resolution elongated CS-LDP (ME-CS-LDP) to solve such problem. By increasing the number of directions, which can be implemented by increasing the sampling points on the ellipse radius with interpolation, multi-resolution elongated CS-LDP can provide more discriminant information on more directions. Furthermore, our proposed multi-resolution elongated CS-LDP is defined in ellipse field to depict some important ellipse part of faces, like eyes and mouth. Gabor filter plus ME-CS-LDP/weighed ME-CS-LDP is used for face recognition in this paper. The experiment results on the illumination subset of Yale B database, the subset of PIE illumination database and VALID face database have validated the effectiveness of the proposed method.