Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/4040
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dc.creatorYuan, Miaolong-
dc.creatorXie, Ming-
dc.creatorYin, Xiaoming-
dc.date2003-12-23T15:25:26Z-
dc.date2003-12-23T15:25:26Z-
dc.date2002-01-
dc.date.accessioned2013-10-09T02:33:57Z-
dc.date.available2013-10-09T02:33:57Z-
dc.date.issued2013-10-09-
dc.identifierhttp://hdl.handle.net/1721.1/4040-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/1721-
dc.descriptionFeature matching in images plays an important role in computer vision such as for 3D reconstruction, motion analysis, object recognition, target tracking and dynamic scene analysis. In this paper, we present a robust cooperative strategy to establish the correspondence of the contours between two uncalibrated images based on the recovered epipolar geometry. We take into account two representations of contours in image as contour points and contour chains. The method proposed in the paper is composed of the following two consecutive steps: (1) The first step uses the LMedS method to estimate the fundamental matrix based on Hartley’s 8-point algorithm, (2) The second step uses a new robust cooperative strategy to match contours. The presented approach has been tested with various real images and experimental results show that our method can produce more accurate contour correspondences.-
dc.descriptionSingapore-MIT Alliance (SMA)-
dc.format165741 bytes-
dc.formatapplication/pdf-
dc.languageen_US-
dc.relationInnovation in Manufacturing Systems and Technology (IMST);-
dc.subjectfeature matching-
dc.subjectcontour matching-
dc.subjectepipolar geometry-
dc.subjectLMedS method-
dc.titleRobust Cooperative Strategy for Contour Matching Using Epipolar Geometry-
dc.typeArticle-
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