Improved Gradientface used in face recognition under varying illumination

In this paper, an improved Gradientface method is proposed for face recognition under varying illumination. It uses the gradient angle as the input feature. It generates the gradient vectors in difference form, and then computes the gradient angle. The gradient angle which is computed by differential equation preserves the detailed image information and it is proved to be most insensitive to the illumination. Then, the statistical relationships among angles of samples are used for classifier. The cosine distance is the cosine of angle between vectors and then it computes the distance in the gradient domain. Therefore, it achieves the best performance for our method. According to the experimental results, our method outperforms conventional methods under varying illuminations, especially in the large scale face database.