Paper
8 February 2017 An improved RANSAC algorithm for line matching on multispectral images
Lijun Wei, Yong Li, Hang Yu, Liangpeng Xu, Chunxiao Fan
Author Affiliations +
Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 1022507 (2017) https://doi.org/10.1117/12.2266462
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lijun Wei, Yong Li, Hang Yu, Liangpeng Xu, and Chunxiao Fan "An improved RANSAC algorithm for line matching on multispectral images", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 1022507 (8 February 2017); https://doi.org/10.1117/12.2266462
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Cited by 1 scholarly publication.
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KEYWORDS
Multispectral imaging

Einsteinium

Image processing

3D modeling

Data modeling

Image segmentation

Visualization

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