Abstract
Face recognition system is an important area of human biometrics and a successful application of pattern recognition. Variable illumination conditions in face images are main obstacle in face recognition systems. To deal with this problem, this paper presents robust illumination-insensitive pre-processing, Zernike Moments-based feature extraction and L1-norm distance method. In pre-processing the input face image is transformed into an illumination-insensitive image by integral normalised gradient image (INGI) method. Features are extracted by Zernike Moments. Finally, face recognition task is performed by L1-norm distance measurement. Experimental tests on the CMU-PIE face database are performed. The proposed method shows 84% verification rate under different illuminations.
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