In this paper we present a new method for point matching in stereoscopic color images. Our approach consists first in characterizing points of interest using differential invariants. Then we define additional first order invariants using color information, which make sufficient the characterization till first order. In addition, we make our description robust to important image transformations like rotation, range of viewpoint and linear illumination variations. Second, we propose a new incremental technique for point matching using our characterization, which works robustly and rapidly whatever the number of points to be matched. Our stereo matching scheme is evaluated using stereo color images, with viewpoint and illumination variations. The very good results obtained clearly show the pertinence of our approach. Our color characterization produces a high rate of good matches, even though only first order derivatives are used. Results on images holding many points show that our matching process is robust and rapidly implemented even if the points to be matched are numerous. It is a great asset, when matching a high set of points is necessary for example to realize dense depth maps between images.
Keywords:
Color Images, Differential Invariants, Stereo Matching, Transfer Methods
