Modified Hough transform for images containing many textured regions

Yun Seok Lee, Seung Hun Yoo, Chang Sung Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Images which have a lot of textured regions make the result of Hough transform (HT) very poor. This paper presents an improved HT that deals with such a textured image by diminishing the effect of noise edges and using weighted voting score. The method first eliminates the noise edges resulted from textured regions; then, the method casts votes for edges upon the accumulator array with weight score in accordance with the number of sequential votes. Our modified HT is efficient in that it produces important lines first such as verge of building, avoiding improper lines taken from the noise edges.

Original languageEnglish
Title of host publicationRough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings
PublisherSpringer Verlag
Pages824-833
Number of pages10
ISBN (Print)3540476938, 9783540476931
DOIs
Publication statusPublished - 2006
Event5th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006 - Kobe, Japan
Duration: 2006 Nov 62006 Nov 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4259 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006
CountryJapan
CityKobe
Period06/11/606/11/8

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Lee, Y. S., Yoo, S. H., & Jeong, C. S. (2006). Modified Hough transform for images containing many textured regions. In Rough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings (pp. 824-833). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4259 LNAI). Springer Verlag. https://doi.org/10.1007/11908029_85