Advanced weight graph transformation matching algorithm. Issue 6 (1st December 2015)

• Record Type: Journal Article
• Authors: Wang, Song; Guo, Xin; Mu, Xiaomin; Huo, Yahong; Qi, Lin
• Is Part Of: IET computer vision. Volume 9:Issue 6(2015)
• Page Start: 960
• Page End: 966
• Publication Date: 2015-12-01
• Subjects: graph theory -- image matching; advanced weight graph transformation matching algorithm -- point matching algorithm -- AWGTM algorithm -- iterative correspondence reservation -- angular distance -- nearest-neighbour graphs -- outlier elimination -- inlier reservation -- pattern duplication -- nonrigid object deformation -- outlier rates; Computer vision -- Periodicals; Pattern recognition systems -- Periodicals; 006.37
• DOI: 10.1049/iet-cvi.2014.0339
• Languages: English
• ISSNs: 1751-9632

Abstract

Abstract : An efficient and accurate point matching algorithm named advanced weight graph transformation matching (AWGTM) is proposed in this study. Instead of relying only on the elimination of dubious matches, the method iteratively reserve correspondences which have a small angular distance between two nearest‐neighbour graphs. The proposed algorithm is compared against weight graph transformation matching (WGTM) and graph transformation matching (GTM). Experimental results demonstrate the superior performance in eliminating outliers and reserving inliers of AWGTM algorithm under various conditions for images, such as duplication of patterns and non‐rigid deformation of objects. An execution time comparison is also presented, where AWGTM shows the best results for high outlier rates.