Paper Title
Increasing Accuracy of Face Recognition using Based Graph Structure

Abstract
Face recognition attracts much attention during recent years due to its many applications in different fields such as security systems, entertainment, criminal identification and etc. Although many face recognition techniques have been proposed and many achievements have been obtained, we can’t get high recognition rate due to the changes of pose, illumination, and expression. In this article, a new approach for face recognition is proposed based on the local graph structure. Each pixel is represented with a graph structure of its neighbours' pixels. The histograms of the proposed approach were used for recognition by using the nearest neighbour classifiers that include Euclidean distance, correlation coefficient and chi-square distance measures. Senthilkumar faceand Yale face databases were used to be experimented with the proposed method. The proposed approach is robust to variation in term of facial expressions, facial details, and illumination. Keywords - Face recognition, Pattern recognition, Local Binary Patten, Nearest Neighbour, Local Graph Structure.