Title :
CTFDP: an affine invariant method for matching contours
Author :
Tang, Hui-Xuan ; Wei, Hui
Author_Institution :
Dept. of Comput. Sci. & Eng., Fudan Univ., Shanghai, China
Abstract :
In this paper a new method for matching contours called CTFDP is presented. It is invariant to affine transformations and can provide robust and accurate estimation of point correspondence between closed curves. This has all been achieved by exploiting the dynamic programming techniques in a coarse-to-fine framework. By normalizing the shape into a standard point distribution, the new method can compare different shapes despite the shearing and scaling effect of affine transformation. Using the coarse-to-fine dynamic programming technique, the shapes are aligned to each other by iteratively seeking for correspondences and estimating relative transformations so as to prune the start points in the dynamic programming stage in turn. Experiments on artificial and real images have validated the robustness and accuracy of the presented method.
Keywords :
affine transforms; computer vision; dynamic programming; image matching; contour matching; dynamic programming; invariant affine transformation; real image; robust estimation; coarse-to-fine strategy; contour matching; dynamic programming;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527840