Modified after surgical face recognition using RBF neural networks and local Gabor binary patterns

Today, a typical face recognition system, especially after surgeries are having problems such as lack of identification of the tissue changes are attributed to the original image. In this paper, a method is proposed to solve this problem as GLRB¹. In the proposed method, the image is classification by RBF² neural network after normalized, then extracted the face texture feature with Gabor filters and LBP. The Characteristics of proposed method that used the filter bank to images are more fit after surgery. The Results execution after surgical on the images, show that the proposed method has satisfactory performance.