A straight line detection using principal component analysis

Yun Seok Lee, Han S. Koo, Chang-Sung Jeong

Research output: Contribution to journalArticle

69 Citations (Scopus)

Abstract

A straight line detection algorithm is presented. The algorithm separates row and column edges from edge image using their primitive shapes. The edges are labeled, and the principal component analysis (PCA) is performed for each labeled edges. With the principal components, the algorithm detects straight lines and their orientations, which is useful for various intensive applications. Our algorithm overcomes the disadvantages of Hough transform (HT) and other algorithms, i.e. unknown grouping of collinear lines, complexity and local ambiguities. The experimental results show the efficiency of our algorithm.

Original languageEnglish
Pages (from-to)1744-1754
Number of pages11
JournalPattern Recognition Letters
Volume27
Issue number14
DOIs
Publication statusPublished - 2006 Oct 15

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Principal component analysis
Hough transforms

Keywords

  • Edge image
  • Line descriptor
  • Principal component analysis (PCA)
  • Straight line detection

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

A straight line detection using principal component analysis. / Lee, Yun Seok; Koo, Han S.; Jeong, Chang-Sung.

In: Pattern Recognition Letters, Vol. 27, No. 14, 15.10.2006, p. 1744-1754.

Research output: Contribution to journalArticle

Lee, Yun Seok ; Koo, Han S. ; Jeong, Chang-Sung. / A straight line detection using principal component analysis. In: Pattern Recognition Letters. 2006 ; Vol. 27, No. 14. pp. 1744-1754.
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