Recognizing face images under different lighting conditions

We present a new algorithm for recognizing face images under different lighting conditions. Instead of the commonly used methods of modeling the 3D shape or finding some illumination invariant, the basic idea of our algorithm is to create new synthetic images by simulating lighting effects of the input image for each candidate image in the database, and then checking correlation between the input image and the resulting synthesized images. With our method, only a single image is needed for each face in the database, which significantly decreases the size of the database. Theory analysis and experimental results show that this algorithm can strikingly enhance the recognition rate and can be used for real time applications.