This paper presents a new method for matching points of interest in stereoscopic, uncalibrated color images. It consists in characterizing color points using differential invariants. We define additional first order invariants, using color information, and we show that the first order is sufficient to make the characterization accurate. The characterization thus obtained is invariant to orthogonal image transformations. In addition, we make it robust enough for affine illumination transformations. We go on to present a generalization of a gray-level corner detector to the case of color images. Thirdly, we propose a robust and fast incremental technique for matching points of interest in uncalibrated cases, which works robustly and rapidly whatever the number of points to be matched. Our matching scheme is evaluated using stereo color images consisting of many points, with viewpoint and illumination variations. The results obtained clearly show the relevance of our approach. © 2000 Elsevier Science B.V. All rights reserved.
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