Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/756
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dc.contributor.authorNachar, Rabihen_US
dc.contributor.authorInaty, Elieen_US
dc.contributor.authorBonnin, Patrick Jen_US
dc.contributor.authorAlayli, Yasseren_US
dc.date.accessioned2020-12-23T08:36:20Z-
dc.date.available2020-12-23T08:36:20Z-
dc.date.issued2014-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/756-
dc.description.abstractA new algorithm to detect straight edge parts which form the contour of an object presented in an image is discussed in this paper. This algorithm is very robust and can detect true straight edges even when their pixel's locations are not straight due to natural noise at the object borders. These straight edges are than used to report and classify contour's corners according to their angle and their adjacent segments lengths. A new technique for polygonal approximation is also presented to find the best set among these corners to construct the polygon vertices that best describe the approximating contour. It starts by eliminating the corners, one after the other using Iterative Corner Suppression (ICS) process. This in turn enables us to obtain the smallest possible error in the approximation. Experimental results demonstrate the efficiency of this technique in comparison with recently proposed algorithms.en_US
dc.format.extent10 p.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.subjectStraight edgesen_US
dc.subjectCornersen_US
dc.subjectPolygonal Approximationen_US
dc.subjectContouren_US
dc.titlePolygonal approximation of an object contour by detecting edge dominant corners using iterative corner suppressionen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Computer Vision Theory and Applications (VISAPP) (9th : 5-8 Jan. 2014 : Lisbon, Portugal)en_US
dc.contributor.affiliationDepartment of Telecommunications and Networking Engineeringen_US
dc.contributor.affiliationDepartment of Electrical Engineeringen_US
dc.description.startpage247en_US
dc.description.endpage256en_US
dc.date.catalogued2018-01-29-
dc.description.statusPublisheden_US
dc.identifier.OlibID177195-
dc.identifier.openURLhttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7294818en_US
dc.relation.ispartoftextInternational Conference on Computer Vision, Theory and Applicationsen_US
dc.provenance.recordsourceOliben_US
crisitem.author.parentorgFaculty of Engineering-
Appears in Collections:Department of Telecommunications and Networking Engineering
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