Detecting line segments in an image- A new implementation for Hough Transform

Yu-Tai Ching*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

The conventional Hough Transform is a technique for detecting line segments in an image. The conventional Hough Transform transforms image points into lines in the parameter space. If there are collinear image points, the lines transformed from the points intersect at a point in the parameter space. Determining the intersection is generally carried out through the "voting method", which partitions the parameter space into squared meshes. A problem with the voting method involves determining the resolution required for partitioning the parameter space. In this paper, we present a solution to this problem. We propose to transform an image point into a belt, whose width is a function of the width of a line in the image. We then determine the intersection of numerous belts to detect a line segment. An iterated algorithm based the transformation for detecting line segments is presented in this paper.

Original languageEnglish
Pages (from-to)421-429
Number of pages9
JournalPattern Recognition Letters
Volume22
Issue number3-4
DOIs
StatePublished - 1 Mar 2001

Keywords

  • Computational geometry
  • Geometric duality
  • Hough Transform

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