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Proceedings Paper

An improved RANSAC algorithm for line matching on multispectral images
Author(s): Lijun Wei; Yong Li; Hang Yu; Liangpeng Xu; Chunxiao Fan
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Paper Abstract

This paper proposes a method for removing mismatched lines on multispectral images. The inaccurate detection of ending points brings a great challenge for matching lines since corresponding lines may not be integrally extracted. Due to the inaccurate detection of ending points, lines are usually mismatched with the line description. To eliminate the mismatched lines, we employ a modified RANSAC (Random Sample Consensus) consisting of two steps: (1) pick three line matches randomly and determine their intersections, which are used to calculate a transformation; (2) the best transformation is obtained by sorting the matching score of line matches and then the inliers are declared as the correct matches. Experimental results show that the proposed method can effectively remove incorrect matches on multispectral images.

Paper Details

Date Published: 8 February 2017
PDF: 5 pages
Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 1022507 (8 February 2017); doi: 10.1117/12.2266462
Show Author Affiliations
Lijun Wei, Beijing Univ. of Posts and Telecommunications (China)
Yong Li, Beijing Univ. of Posts and Telecommunications (China)
Hang Yu, Beijing Univ. of Posts and Telecommunications (China)
Liangpeng Xu, Beijing Univ. of Posts and Telecommunications (China)
Chunxiao Fan, Beijing Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 10225:
Eighth International Conference on Graphic and Image Processing (ICGIP 2016)
Yulin Wang; Tuan D. Pham; Vit Vozenilek; David Zhang; Yi Xie, Editor(s)

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