Deep convolutional neural network applies to face recognition in small and medium databases

This paper proposes a method combining local binary patterns (LBP) and deep convolution neural network. This paper extracts LBP features of face image as an input of CNN, and train the CNN network with the LBP features, then use the trained network for face recognition, so that we can get rid of disadvantages of poor stability of CNN gray scale and identify the trained CNN network more effectively. This algorithm has been experimented on several common face libraries, Indicating that its performance than the traditional methods and general deep learning methods have improved.