A Novel Linelet-Based Representation for Line Segment Detection
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, Nam-Gyu | - |
dc.contributor.author | Yuille, Alan | - |
dc.contributor.author | Lee, Seong-Whan | - |
dc.date.accessioned | 2021-09-02T12:25:02Z | - |
dc.date.available | 2021-09-02T12:25:02Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2018-05 | - |
dc.identifier.issn | 0162-8828 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/76004 | - |
dc.description.abstract | This paper proposes a method for line segment detection in digital images. We propose a novel linelet-based representation to model intrinsic properties of line segments in rasterized image space. Based on this, line segment detection, validation, and aggregation frameworks are constructed. For a numerical evaluation on real images, we propose a new benchmark dataset of real images with annotated lines called YorkUrban-LineSegment. The results show that the proposed method outperforms state-of-the-art methods numerically and visually. To our best knowledge, this is the first report of numerical evaluation of line segment detection on real images. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE COMPUTER SOC | - |
dc.subject | HOUGH TRANSFORM | - |
dc.title | A Novel Linelet-Based Representation for Line Segment Detection | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Seong-Whan | - |
dc.identifier.doi | 10.1109/TPAMI.2017.2703841 | - |
dc.identifier.scopusid | 2-s2.0-85044856825 | - |
dc.identifier.wosid | 000428901200014 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, v.40, no.5, pp.1195 - 1208 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
dc.citation.title | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
dc.citation.volume | 40 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 1195 | - |
dc.citation.endPage | 1208 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | HOUGH TRANSFORM | - |
dc.subject.keywordAuthor | Intrinsic properties of digital line | - |
dc.subject.keywordAuthor | probabilistic line segment representation | - |
dc.subject.keywordAuthor | line segment validation | - |
dc.subject.keywordAuthor | image edge detection | - |
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