Hough transform with dynamic thresholding for robust and real-time detection of complex curves in images

Shen En Shih, Wen-Hsiang Tsai 

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A dynamic thresholding method is proposed for use in the Hough transform to detect complex curves in images robustly. While determining edge pixels contributing to the peak in the Hough space for detecting a curve with noise and other errors, the proposed method can endure the errors by detecting pixels coming from an equal-width shape which is centered at the curve with a small width everywhere along the curve. This equal-width shape detection capability is accomplished by the use of a dynamic threshold for pixel selection, which is derived from the use of the first-order directional derivative of the function describing the curve. Three conventional methods are compared to show the superiority in robustness of the proposed method via experimental results, and a real-time application of the method for quick detection of lines in omni-images is also demonstrated.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages1454-1458
Number of pages5
DOIs
StatePublished - 18 Oct 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 26 May 201331 May 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period26/05/1331/05/13

Keywords

  • Hough transform
  • Image signal processing
  • real-time application
  • shape detection

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