Share Email Print
cover

Proceedings Paper

Line segment detection via random line fitting
Author(s): Ke Shang; Tao Lei; Quan Wang; Yu Zhang; Hao Zhang; Jinwen Tian
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper 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.

Paper Details

Date Published: 14 February 2020
PDF: 11 pages
Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114301Y (14 February 2020); doi: 10.1117/12.2541909
Show Author Affiliations
Ke Shang, Tianjin Jinhang Institute of Technical Physics (China)
Tao Lei, Tianjin Jinhang Institute of Technical Physics (China)
Tianjin Infrared Imaging Technology Engineering Ctr. (China)
Quan Wang, Tianjin Jinhang Institute of Technical Physics (China)
Yu Zhang, Tianjin Jinhang Institute of Technical Physics (China)
Hao Zhang, Tianjin Jinhang Institute of Technical Physics (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11430:
MIPPR 2019: Pattern Recognition and Computer Vision
Nong Sang; Jayaram K. Udupa; Yuehuan Wang; Zhenbing Liu, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray