TY - JFULL AU - Sanghoon Kim and Sun-Tae Chung and Souhwan Jung and Seongwon Cho PY - 2008/2/ TI - An Improved Illumination Normalization based on Anisotropic Smoothing for Face Recognition T2 - International Journal of Computer and Information Engineering SP - 1 EP - 8 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/3973 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 13, 2008 N2 - Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an improved illumination normalization method for face recognition. Illumination normalization algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates the intensity contrast of the original image, and incurs less sharp edges. The proposed method in this paper improves the previous anisotropic smoothing-based illumination normalization method so that it increases the intensity contrast and enhances the edges while diminishing the effect of illumination variations. Due to the result of these improvements, face images preprocessed by the proposed illumination normalization method becomes to have more distinctive feature vectors (Gabor feature vectors) for face recognition. Through experiments of face recognition based on Gabor feature vector similarity, the effectiveness of the proposed illumination normalization method is verified. ER -