Line segment detection via random line fitting

Ke Shang; Tao Lei; Quan Wang; Yu Zhang; Hao Zhang; Jinwen Tian

doi:10.1117/12.2541909

14 February 2020 Line segment detection via random line fitting

Ke Shang, Tao Lei, Quan Wang, Yu Zhang, Hao Zhang, Jinwen Tian

Author Affiliations +

Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 114301Y (2020) https://doi.org/10.1117/12.2541909
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

In this study we propose a line segment detector that generates accurate results. The proposed algorithm, which is linear-time for the number of edge pixels, provides highly accurate result and does not break off at cross points. The proposed algorithm starts from a randomly selected pixel and uses the improved least-square fitting method. This improved method is designed to process incremental data in linear-time. The proposed algorithm is highly suitable for the vision measurement and camera calibration applications.

Citation Download Citation

Ke Shang, Tao Lei, Quan Wang, Yu Zhang, Hao Zhang, and Jinwen Tian "Line segment detection via random line fitting", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114301Y (14 February 2020); https://doi.org/10.1117/12.2541909

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