Abstract The face recognition technology is one of the most important methods in the biometric - based authentication technology. Automatic authentication based on face recognition has important theoretical significance and application value, it is also a hot research directions in the field puter vision. However, under the non-binding environment, due to the illumination, occlusion, facial expressions, and age change factors, the recognition rate and robustness of the face recognition system is still not satisfactory. This paper introduces monly used face recognition algorithm, and also introduces the basic application and principles of the Gabor wavelet and LBP operator. Make full use of the advantages of the Gabor wavelet and local binary patterns, a more stable and better expression of the face has been proposed. The innovation of the algorithm is that information jointly contained in image space, scale and orientation domains can provide more fully human facial feature extraction and improve the performance of the recognition systems. Secondly, statistical uniform pattern of LBP has been proposed based on the unique characteristics for different images. Unlike the method proposed by Ojala that the vast number of LBP mode contains only up to twice from 0-1 or 1-0 transition, we adopt a more general strategy and define the uniform pattern in a iterative way. In each step, the patterns corresponding to the two smallest occurrence percentage collapse into a single one and then the histogram in resorted. Eventually reduce the dimensions of the data. Finally, we use of PCA and FLDA linear classification algorithm for classification. Experimental results show that the algorithm can effectively improve the recognition rate. Keywords: Face recognition Gabor wavelet Local binary pattern(LBP) PCA LDA 目 录 摘 要............................................................................................................... I Abstract.....................................
