A robust and fast line segment detector based on top-down smaller eigenvalue analysis

Dong Liu; Yongtao Wang; Zhi Tang; Xiaoqing Lu

doi:10.1117/12.2050864

10 January 2014 A robust and fast line segment detector based on top-down smaller eigenvalue analysis

Dong Liu, Yongtao Wang, Zhi Tang, Xiaoqing Lu

Proceedings Volume 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013); 906916 (2014) https://doi.org/10.1117/12.2050864
Event: Fifth International Conference on Graphic and Image Processing, 2013, Hong Kong, China

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.

Citation Download Citation

Dong Liu, Yongtao Wang, Zhi Tang, and Xiaoqing Lu "A robust and fast line segment detector based on top-down smaller eigenvalue analysis", Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 906916 (10 January 2014); https://doi.org/10.1117/12.2050864

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