Improving the Face Recognition system by hybrid image reprocessing

In this paper we present a framework for improving face recognition system that have several stages. Some improvements of every stage are very important to the recognition results. Driven by this intuition, we proposed a novel scheme that gives the system a better performance. The scheme including dataset augment for learning, especially for big data requirement of deep learning. Enhancing the image contrast ratio and rotate the image for several angles that can improve the detection accuracy. Then, cropping the face in appropriate area for feature extraction and getting the optimal feature vector for face recognition at last.