Table of Contents
ISRN Machine Vision
Volume 2013, Article ID 516052, 10 pages
Research Article

A Robust Illumination Normalization Method Based on Mean Estimation for Face Recognition

1School of Communication and Information Engineering, Shanghai University, 99 Shangda Road, Shanghai, China
2Key Laboratory of Advanced Displays and System Application, Ministry of Education, 99 Shangda Road, Shanghai, China

Received 17 September 2013; Accepted 19 November 2013

Academic Editors: A. Bandera, O. Ghita, M. Leo, and S. Mattoccia

Copyright © 2013 Yong Luo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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