[IPOL announce] new article: Iterative Hough Transform for Line Detection in 3D Point Clouds

[announcements about the IPOL journal]

A new article is available in IPOL: http://www.ipol.im/pub/art/2017/208/

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

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.