Direct image alignment for active near infrared image differencing

Abstract

One of the difficult challenges in face recognition is dealing with the illumination variations that occur in varying environments. A practical and efficient way to address harsh illumination variations is to use active image differencing in near-infrared frequency range. In this method, two types of image frames are taken: an illuminated frame is taken with near infrared illumination, and an ambient frame is taken without the illumination. The difference between face regions of these frames reveals the face image illuminated only by the illumination. Therefore the image is not affected by the ambient illumination and illumination robust face recognition can be achieved. But the method assumes that there is no motion between two frames. Faces in different locations on the two frames introduces a motion artifact. To compensate for motion between two frames, a motion interpolation method has been proposed; but it has limitations, including an assumption that the face motion is linear. In this paper, we propose a new image alignment method that directly aligns the actively illuminated and ambient frames. The method is based on Lucas-Kanade parametric image alignment method and involves a new definition of errors based on the properties of the two types of frames. Experimental results show that the direct method outperforms the motion interpolation method in terms of face recognition rates.