Face Recognition Based On Gabor Local Feature and Convolutional Neural Network

Since the distribution of kernel function of Gabor transform and the Two-Dimensional receptive field profiles of mammalian simple cells in the primary visual cortex is very similar, and has the direction selectivity and good spatial locality, so the acquisition of spatial scale information of multiple directions and local structure features in the local regions of images provide a more effective method. The method is based on the Gabor transform and fused the convolutional neural network of the powerful learning ability. The local features of the Gabor transform is used as the input of the neural network, the neural network is used to classify the samples. In ORL face database, the experimental results show that the face recognition methods based on Gabor local features and convolutional neural network in the same conditions obtain higher face recognition rate and the robustness.