Abstract: In recent years, Local Binary Pattern (LISP) has been successfully applied to face recognition. However, the dimensionality of the feature vector extracted by LISP is usually very high. On the contrary, Center-Symmetric Local Binary Pattern (CS-LBP) encodes the image with the technique of Center Symmetry. As a result,CS-LBP can largely reduce the extracted feature dimension. Therefore, in this paper, CS-LISP was employed to extract features from facial images,and then a new face recognition algorithm based on multi channel Gabor filtering (MCGF) and CS-;BP was brought forward. Experimental results on Yale, ORL and FETER face databases demonstrate that compared with LBP,CS-LISP can achieve the comparable performance in terms of recognition rate with lower feature dimensionality. Additionally, CS-LBP based on MCGF can increase the accuracy obviously.

Key words: Ccnter-symmetric local binary pattern,Multi-channel Gabor filtering,Fcature cxtraction,Face recognition