Differential invariants for color images

We present in this paper a new method for matching points in stereoscopic color images, based on color diierential invariants involving only rst order derivatives of images. Our method is able to match robustly the images even if they present important transformations like rotation, range of viewpoint and change of intensity between each other. We present here a generalization of a gray level corner detector to the case of color images. This detector is robust and allows us to extract point primitives in stereoscopic images to be matched together, only with rst order derivatives. We then describe these points with our set of local color invariants, and we propose a simple and eecient scheme for matching them. The robustness of the matching against local deformations is shown using deformations of single color images, then our stereo matching scheme is evaluated using true stereo color images with viewpoint variations. The results obtained on complex scenes clearly show the pertinence of our approach. We show that color information greatly improves the matching method, according to the fact that the additional features allow us to use only derivatives till rst order.