Face Recognition Based on Local Feature Analysis

This paper presents a new face recognition method based on the analysis of local features. Firstly, we can get the images of magnitude by means of analyzing face images with the Gabor wavelets. Secondly, the magnitude images are divided into blocks, then principle components analysis (PCA) could be directly used to all the blocks to construct the feature space. Finally, all the blocks of images are projected to the feature space and get the face feature vectors. By counting and analyzing the feature vector, we get the recognition results. The experimental results show that this method uses the advantages of Gabor wavelets and local feature analysis (LFA), has a good recognition capability.