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dc.contributor.authorChing, YTen_US
dc.date.accessioned2014-12-08T15:44:08Z-
dc.date.available2014-12-08T15:44:08Z-
dc.date.issued2001-03-01en_US
dc.identifier.issn0167-8655en_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0167-8655(00)00130-6en_US
dc.identifier.urihttp://hdl.handle.net/11536/29808-
dc.description.abstractThe conventional Hough Transform is a technique for detecting line segments in an image. The conventional Hough Transform transforms image points into lines in the parameter space. If there are collinear image points, the lines transformed from the points intersect at a point in the parameter space. Determining the intersection is generally carried out through the "voting method", which partitions the parameter space into squared meshes. A problem with the voting method involves determining the resolution required for partitioning the parameter space. Tn this payer. we present a solution to this problem. We propose to transform an image point into a belt, whose width is a function of the width of a line in the image. We then determine the intersection of numerous belts to detect a line segment. An iterated algorithm based the transformation for detecting line segments is presented in this paper. (C) 2001 Elsevier Science B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectHough transformen_US
dc.subjectcomputational geometryen_US
dc.subjectgeometric dualityen_US
dc.titleDetecting line segments in an image - a new implementation for Hough Transformen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0167-8655(00)00130-6en_US
dc.identifier.journalPATTERN RECOGNITION LETTERSen_US
dc.citation.volume22en_US
dc.citation.issue3-4en_US
dc.citation.spage421en_US
dc.citation.epage429en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000167983900015-
dc.citation.woscount23-
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