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 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 824-833 |
| Number of pages | 10 |
| Volume | 4259 LNAI |
| Publication status | Published - 2006 Dec 11 |
| 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) | 03029743 |
| ISSN (Electronic) | 16113349 |
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 |
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ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
- Computer Science(all)
- Theoretical Computer Science
Cite this
Modified Hough transform for images containing many textured regions. / Lee, Yun Seok; Yoo, Seung H.; Jeong, Chang-Sung.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4259 LNAI 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
}
TY - GEN
T1 - Modified Hough transform for images containing many textured regions
AU - Lee, Yun Seok
AU - Yoo, Seung H.
AU - Jeong, Chang-Sung
PY - 2006/12/11
Y1 - 2006/12/11
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=33845245067&partnerID=8YFLogxK
M3 - Conference contribution
SN - 3540476938
SN - 9783540476931
VL - 4259 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 824
EP - 833
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -