3 February 2011 An improved RANSAC algorithm using within-class scatter matrix for fast image stitching
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Abstract
An improved RANSAC algorithm using within-class scatter matrix for fast image stitching is proposed in this paper. First, features described by SIFT are extracted. Next, the Min-cost K-flow algorithm is used to match SIFT points in different images. Then, the improved RANSAC algorithm with the within-class scatter matrix is used to divide the matching feature points into two classes: inliers and outliers. Finally, the homography is computed in the set of inliers. Experiment results show that the improved algorithm can increase the registration speed by some 20 percent with the same accuracy and robustness comparing to the original RANSAC algorithm.
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Lin Zhang, Lin Zhang, Zhihua Liu, Zhihua Liu, Jianbin Jiao, Jianbin Jiao, } "An improved RANSAC algorithm using within-class scatter matrix for fast image stitching", Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 787017 (3 February 2011); doi: 10.1117/12.876626; https://doi.org/10.1117/12.876626
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