An illumination normalization method for face recognition has been developed since it was difficult to control lighting conditions\r\nefficiently in the practical applications. Considering that the irradiation light is of little variation in a certain area, a mean estimation\r\nmethod is used to simulate the illumination component of a face image. Illumination component is removed by subtracting the\r\nmean estimation from the original image. In order to highlight face texture features and suppress the impact of adjacent domains,\r\na ratio of the quotient image and its modulus mean value is obtained.The exponent result of the ratio is closely approximate to a\r\nrelative reflection component. Since the gray value of facial organs is less than that of the facial skin, postprocessing is applied to\r\nthe images in order to highlight facial texture for face recognition. Experiments show that the performance by using the proposed\r\nmethod is superior to that of state of the arts.
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