A Simple Illumination Normalization Algorithm for Face Recognition

Most of the FR (face recognition) systems suffer from sensitivity to variations in illumination. For better performance the FR system needs more training samples acquired under variable lightings but it is not practical in real world. We introduce a novel pre-processing method, which makes illumination-normalized face image for face recognition. The proposed method, ICR (Illumination Compensation based on Multiple Regression Model), is to find the plane that best fits the intensity distribution of the face image using the multiple regression model, then use this plane to normalize the face image. The advantages of our method are simple and practical. The planar approximation of a face image is mathematically defined by the simple linear model. We provide experimental results to demonstrate the performance of the proposed ICR method on public face databases and our database. The experiments show a significant improvement of the recognition rate.

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