Modified Hough transform for images containing many textured regions

Yun Seok Lee; Seung Hun Yoo; Chang Sung Jeong

doi:10.1007/11908029_85

Modified Hough transform for images containing many textured regions

Yun Seok Lee, Seung Hun Yoo, Chang Sung Jeong

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Rough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings
Publisher	Springer Verlag
Pages	824-833
Number of pages	10
ISBN (Print)	3540476938, 9783540476931
DOIs	https://doi.org/10.1007/11908029_85
Publication status	Published - 2006
Event	5th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006 - Kobe, Japan Duration: 2006 Nov 6 → 2006 Nov 8

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4259 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	5th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006
Country	Japan
City	Kobe
Period	06/11/6 → 06/11/8

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/11908029_85

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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

Modified Hough transform for images containing many textured regions. / Lee, Yun Seok; Yoo, Seung Hun; Jeong, Chang Sung.

Rough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings. Springer Verlag, 2006. p. 824-833 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4259 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, YS, Yoo, SH & Jeong, CS 2006, Modified Hough transform for images containing many textured regions. in Rough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4259 LNAI, Springer Verlag, pp. 824-833, 5th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006, Kobe, Japan, 06/11/6. https://doi.org/10.1007/11908029_85

Lee YS, Yoo SH, Jeong CS. Modified Hough transform for images containing many textured regions. In Rough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings. Springer Verlag. 2006. p. 824-833. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11908029_85

Lee, Yun Seok ; Yoo, Seung Hun ; Jeong, Chang Sung. / Modified Hough transform for images containing many textured regions. Rough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings. Springer Verlag, 2006. pp. 824-833 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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