Image matching consists in finding in two images the features which represent a same feature of the observed scene. It is a basic process of vision as soon as several images are used. use of local geometric quasi-invariants. Once a first match is made, a projective approximation of the apparent motion and the epipolar geometry may be used to complete it. In the case where we consider more than two images, these images may be matched two by two in a first step, and a global match is deduced in a second step: this is exposed in the last section. The main advantages of the method presented here are the following: it still works even if the images are noisy and the polyhedral approximation of the contours is not exact, if the apparent motion between the images is not very small, if the whole scene has not a single rigid motion, if the camera is not calibrated and the camera motion between the two shots is not known... It is thus usable in many cases where no other method is available