A novel face recognition method,which is a fusion of multi-modal face parts based on Gabor feature(MMP-GF),is proposed in this paper.Firsdy,the bare face image detached from the normalized imagewas convolved with a family of Gabor kernels,and then according to the face structure and the key-pointslocations,the calculated Gabor images were divided into five parts:Gabor face,Gabor eyebrow,Gaboreye,Gabor nose and Gabor mouth.After that multi-modal Gabor features were spatially partitioned intonon-overlapping regions and the averages of regions were concatenated to be a low dimension feature vec-tor,whose dimension was further reduced by principal component analysis(PCA).In the decision levelfusion,match results respectively calculated based on the five parts were combined according to lineardiscriminant analysis(LDA)and a normalized matching algorithm was used to improve the performance.Experiments on FERET database show that the proposed MMP-GF method achieves good robustness to theexpression and age variations.
