Face Recognition Based on Polar Coordinate Transform
Jae-Hyun Oh, Nojun Kwak · Journal of the Institute of Electronics Engineers of Korea · 2010
In this paper, we propose a novel method for face recognition which uses polar coordinate instead of conventional cartesian coordinate. Among the central area of a face, we select a point as a pole and make a polar image of a face by evenly sampling pixels in each direction of 360 degrees around the pole. By applying conventional feature extraction methods to the polar image, the recognition rates are improved. The polar coordinate delineates near-pole area more vividly than the area far from the pole. In a face, important regions such as eyes, nose and mouth are concentrated on the central part of a face. Therefore, the polar coordinate of a face image can achieve more vivid representation of important facial regions compared to the conventional cartesian coordinate. The proposed polar coordinate transform was applied to Yale and FRGC databases and LDA and NLDA were used to extract features afterwards. The experimental results show that the proposed method performs better than the conventional cartesian images.