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Proceedings Paper

A robust and fast line segment detector based on top-down smaller eigenvalue analysis
Author(s): Dong Liu; Yongtao Wang; Zhi Tang; Xiaoqing Lu
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Paper Abstract

In this paper, we propose a robust and fast line segment detector, which achieves accurate results with a controlled number of false detections and requires no parameter tuning. It consists of three steps: first, we propose a novel edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input image; second, we propose a top-down scheme based on smaller eigenvalue analysis to extract line segments within each obtained edge segment; third, we employ Desolneux et al.’s method to reject false detections. Experiments demonstrate that it is very efficient and more robust than two state of the art methods—LSD and EDLines.

Paper Details

Date Published: 10 January 2014
PDF: 5 pages
Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 906916 (10 January 2014); doi: 10.1117/12.2050864
Show Author Affiliations
Dong Liu, Peking Univ. (China)
Yongtao Wang, Peking Univ. (China)
Zhi Tang, Peking Univ. (China)
Xiaoqing Lu, Peking Univ. (China)

Published in SPIE Proceedings Vol. 9069:
Fifth International Conference on Graphic and Image Processing (ICGIP 2013)
Yulin Wang; Xudong Jiang; Ming Yang; David Zhang; Xie Yi, Editor(s)

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