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DC poleHodnotaJazyk
dc.contributor.authorIwanowski, Marcin
dc.contributor.authorGrzabka, Marcin
dc.contributor.editorSkala, Václav
dc.date.accessioned2021-09-01T08:27:59Z
dc.date.available2021-09-01T08:27:59Z
dc.date.issued2021
dc.identifier.citationWSCG 2021: full papers proceedings: 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 299-308.en
dc.identifier.isbn978-80-86943-34-3
dc.identifier.issn2464-4617
dc.identifier.issn2464–4625(CD/DVD)
dc.identifier.urihttp://hdl.handle.net/11025/45036
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.rights© Václav Skala - UNION Agencycs
dc.subjectpodobnost obrazucs
dc.subjectdetekce symetriecs
dc.subjectdetekce objektůcs
dc.subjectfuzzy logikacs
dc.titleSimilarity and symmetry measures based on fuzzy descriptors of image objects’ compositionen
dc.typeconferenceObjecten
dc.typekonferenční příspěvekcs
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThe paper describes a method for measuring the similarity and symmetry of an image annotated with boundingboxes indicating image objects. The latter representation became popular recently due to the rapid development offast and efficient deep-learning-based object-detection methods. The proposed approach allows for comparing setsof bounding boxes to estimate the degree of similarity of their underlying images. It is based on the fuzzy approachthat uses the fuzzy mutual position (FMP) matrix to describe spatial composition and relations between boundingboxes within an image. A method of computing the similarity of two images described by their FMP matrices isproposed and the algorithm of its computation. It outputs the single scalar value describing the degree of content-based image similarity. By modifying the method’s parameters, instead of similarity, the reflectional symmetry ofobject composition may also be measured. The proposed approach allows for measuring differences in objects’composition of various intensities. It is also invariant to translation and scaling and – in case of symmetry detection– position and orientation of the symmetry axis. A couple of examples illustrate the method.en
dc.subject.translatedimage similarityen
dc.subject.translatedsymmetry detectionen
dc.subject.translatedobject detectionen
dc.subject.translatedfuzzy logicen
dc.identifier.doihttps://doi.org/10.24132/CSRN.2021.3101.33
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG 2021: Full Papers Proceedings

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