Fast and robust techniques for detecting straight line segments using local models

Ron Shpilman*, Victor Brailovsky

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

A new line parameterization model, based on Hough transform, offers robust identification of straight lines using geometrical features of lines. The article presents a new algorithm, based on this model, that achieves fast linear (in the number of edge points) detection of line segments, using a fixed small one-dimensional parameter space. The work provides schemes for easy parallel processing and prediction accelaration. The work also suggests a novel contour segmentation technique for filtering out outlier noise, and linking contour edge points at linear time. Results on several real and synthetic images are demonstrated and compared with Random Hough Transform.

Original languageEnglish
Pages (from-to)865-877
Number of pages13
JournalPattern Recognition Letters
Volume20
Issue number9
DOIs
StatePublished - 20 Sep 1999

Keywords

  • Contour segmentation
  • Embedded computations
  • Fast line detection
  • Hough transform
  • Parallel scheme

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