Illumination Normalization of Facial Images for Face Recognition

Abstract

In the paper, we focus on how to reconstruct the illumination normalized facial image which can be used to improve the face recognition. Here, we employ a framework to process large-scale and small-scale features image independently. In this frame work, first, we decompose the facial image into a large-scale feature image and a small-scale feature image. Second, once a facial image is decomposed into a large-scale feature image and a small-scale feature image, normalization is then mainly performed on the large-scale feature image. Then, a smooth operator is applied on the small-scale feature image. Finally, we combine the large- and small- scale feature images to generate an illumination normalized facial image. We test our method using Yale B & Extend Yale B database. The experimental result shows that image processed by our method not only has better visual quality, but also can be used to improve the performance of face recognition.