Face Recognition Under Illumination Variation Using Shadow Compensation and Pixel Selection

We propose a robust face recognition method under illumination variation. By using shadow compensation methods, we restore the image of a facial image taken under arbitrary illumination into an image that is similar to the image taken with frontal illumination. Then we apply a pixel selection method to these restored images in order to reduce the noise components, which can interfere with the extraction of discriminant features for face recognition. The experimental results for the CMU-PIE, Yale B and Multi-PIE databases show that the proposed method results in the improvement of recognition performance under illumination variation.