Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/9993
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dc.contributor.authorLindblad J.en
dc.contributor.authorSladoje N.en
dc.date.accessioned2020-03-03T14:36:29Z-
dc.date.available2020-03-03T14:36:29Z-
dc.date.issued2006-01-01en
dc.identifier.isbn3540351531en
dc.identifier.issn03029743en
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/9993-
dc.description.abstractDefuzzification of fuzzy spatial sets by feature distance minimization, recently proposed as an alternative to crisp segmentation, is studied further. Fully utilizing information available in a fuzzy (discrete) representation of a continuous shape, we present an improved defuzzification method, such that the crisp discrete representation of a fuzzy set is generated at an increased spatial resolution, compared to the resolution of the fuzzy set. The correspondence between a fuzzy and a crisp set is established through a distance between their representations based on selected features, where the different resolutions of the images to compare are taken into account. The performance of the method is tested on both synthetic and real images. © Springer-Verlag Berlin Heidelberg 2006.en
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.titleFeature based defuzziflcation at increased spatial resolutionen
dc.typeConference Paperen
dc.identifier.doi10.1007/11774938_11en
dc.identifier.scopus2-s2.0-33746218513en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/33746218513en
dc.relation.lastpage143en
dc.relation.firstpage131en
dc.relation.volume4040 LNCSen
item.grantfulltextnone-
item.fulltextNo Fulltext-
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