Iterative Hough Transform for Line Detection in 3D Point Clouds
Christoph Dalitz, Tilman Schramke, Manuel Jeltsch
→ BibTeX
@article{ipol.2017.208,
    title   = {{Iterative Hough Transform for Line Detection in 3D Point Clouds}},
    author  = {Dalitz, Christoph and Schramke, Tilman and Jeltsch, Manuel},
    journal = {{Image Processing On Line}},
    volume  = {7},
    pages   = {184--196},
    year    = {2017},
    doi     = {10.5201/ipol.2017.208},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2017.208}}
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.

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