Line segment detection via random line fitting
Ke Shang, Tao Leí, Quan Wang, Yu Zhang, Hao Zhang, Jinwen Tian · 2020
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.