Face Recognition under Varying Illumination with Logarithmic Fractal Analysis

Face recognition under illumination variations is a challenging research area. This paper presents a new method based on the log function and the fractal analysis (FA) to produce a logarithmic fractal dimension (LFD) image which is illumination invariant. The proposed FA feature-based method is a very effective edge enhancer technique to extract and enhance facial features such as eyes, eyebrows, nose, and mouth. Our extensive experiments show the proposed method achieves the best recognition accuracy using one image per subject for training when compared to six recently proposed state-of-the-art methods.