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dc.contributor.author유주한-
dc.contributor.author김동환-
dc.contributor.author이석-
dc.contributor.author박성기-
dc.date.accessioned2024-01-20T07:32:36Z-
dc.date.available2024-01-20T07:32:36Z-
dc.date.created2022-01-10-
dc.date.issued2015-03-
dc.identifier.issn1975-6291-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/125682-
dc.description.abstractWe present a robust power transmission lines detection method based on vanishing pointestimation. Vanishing point estimation can be helpful to detect power transmission lines becauseparallel lines converge on the vanishing point in a projected 2D image. However, it is not easy toestimate the vanishing point correctly in an image with complex background. Thus, we first propose avanishing point estimation method on power transmission lines by using a probabilistic votingprocedure based on intersection points of line segments. In images obtained by our system, powertransmission lines are located in a fan-shaped area centered on this estimated vanishing point, andtherefore we select the line segments that converge to the estimated vanishing point as candidate linesegments for power transmission lines only in this fan-shaped area. Finally, we detect the powertransmission lines from these candidate line segments. Experimental results show that the proposedmethod is robust to noise and efficient to detect power transmission lines.-
dc.publisher한국로봇학회-
dc.title확률적인 소실점 추정 기법에 기반한 강인한 송전선 검출 방법-
dc.title.alternativeA Robust Power Transmission Lines Detection Method Based on Probabilistic Estimation of Vanishing Point-
dc.typeArticle-
dc.description.journalClass2-
dc.identifier.bibliographicCitation로봇학회 논문지, v.10, no.1, pp.9 - 15-
dc.citation.title로봇학회 논문지-
dc.citation.volume10-
dc.citation.number1-
dc.citation.startPage9-
dc.citation.endPage15-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.identifier.kciidART001962011-
dc.subject.keywordAuthorpower transmission lines detection-
dc.subject.keywordAuthorvanishing point-
dc.subject.keywordAuthorprobabilistic estimation-
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KIST Article > 2015
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