Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/11646
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dc.contributor.authorTanács A.en_US
dc.contributor.authorDomokos C.en_US
dc.contributor.authorSladoje, Natašaen_US
dc.contributor.authorLindblad J.en_US
dc.contributor.authorKato Z.en_US
dc.date.accessioned2020-03-03T14:45:13Z-
dc.date.available2020-03-03T14:45:13Z-
dc.date.issued2009-11-09-
dc.identifier.isbn3642022294en_US
dc.identifier.issn03029743en_US
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/11646-
dc.description.abstractFuzzy sets and fuzzy techniques are attracting increasing attention nowadays in the field of image processing and analysis. It has been shown that the information preserved by using fuzzy representation based on area coverage may be successfully utilized to improve precision and accuracy of several shape descriptors; geometric moments of a shape are among them. We propose to extend an existing binary shape matching method to take advantage of fuzzy object representation. The result of a synthetic test show that fuzzy representation yields smaller registration errors in average. A segmentation method is also presented to generate fuzzy segmentations of real images. The applicability of the proposed methods is demonstrated on real X-ray images of hip replacement implants. © 2009 Springer Berlin Heidelberg.en
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.titleRecovering affine deformations of fuzzy shapesen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1007/978-3-642-02230-2_75-
dc.identifier.scopus2-s2.0-70350676212-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/70350676212-
dc.description.versionUnknownen_US
dc.relation.lastpage744en
dc.relation.firstpage735en
dc.relation.volume5575 LNCSen
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:Naučne i umetničke publikacije
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