Shadow Compensation Using Fourier Analysis With Application to Face Recognition

Shadows that occur on face images due to illumination variation can change the appearance of a face and degrade face recognition performance. In this paper, we propose a new shadow compensation method based on the Fourier analysis for handling illumination variation. The face image deteriorated by shadow is restored by using the auxiliary magnitude, which compensates for the magnitude of the Fourier transform distorted due to the illumination variation. The experimental results for the CMU-PIE and Yale B databases show that the proposed method results in improved recognition performance under illumination variation.