The improvement in face recognition that can be obtained from the simultaneous availability of normal and near-infrared (NIR) images is quantitatively measured. The authors designed a camera that can perform a simultaneous acquisition of a NIR image and visible images (VI) and therefore built a face database with this camera aiming at comparing the performance of several algorithms on both types of images when illumination variations occur. The authors noticed the stability of the performance of all the tested algorithms on infrared images upon illumination variation, and the improvement in performance that results from the fusion of these two different types of images