Reliable interest point detection under large illumination variations

Most interest point detection algorithms are highly sensitive to illumination variations. This paper presents a method to detect interest points robustly under large photometric changes. The method, which we call contrast invariant feature transform (CIFT), determines salient interest points in an image by calculating and processing contrast signatures. A contrast signature shows the response of an interest point detector with respect to a set of contrast stretching functions. The method is generic and can be used with most interest point detectors. In this paper, we demonstrate how CIFT improves the repeatability rate of the Harris corner detector.