IPOL Journal · Image Processing On Line
- published
- 2017-07-19
- reference
- Christoph Dalitz, Tilman Schramke, and Manuel Jeltsch, Iterative Hough Transform for Line Detection in 3D Point Clouds, Image Processing On Line, 7 (2017), pp. 184–196. https://doi.org/10.5201/ipol.2017.208
Communicated by Bertrand Kerautret
Demo edited by Bertrand Kerautret
Abstract
The Hough transform is a voting scheme for locating geometric objects in point clouds. This paper describes its application for detecting lines in three dimensional point clouds. For parameter quantization, a recently proposed method for Hough parameter space regularization is used. The voting process is done in an iterative way by selecting the line with the most votes and removing the corresponding points in each step. To overcome the inherent inaccuracies of the parameter space discretization, each line is estimated with an orthogonal least squares fit among the candidate points returned from the Hough transform.
Download
- full text manuscript: PDF (527K)
- source code: TGZ
History
- Note from the editor: The source code was updated on March 28, 2018 to fix a wrong return type of 'orthogonal_LSQ', which resulted in missing lines. The original source code can be found here.
- Note from the editor: the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.
