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dc.contributor.authorHagara, M.
dc.contributor.authorKubinec, P.
dc.date.accessioned2020-04-21T09:37:15Z
dc.date.available2020-04-21T09:37:15Z
dc.date.issued2018-12cs
dc.identifier.citationRadioengineering. 2018 vol. 27, č. 4, s. 919-929. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/186783
dc.description.abstractEdge detection is one of the most commonly used procedures in digital image processing. In the last 30-40 years, many methods and algorithms for edge detection have been proposed. This article presents an overview of edge detection methods, the methods are divided according to the applied basic principles. Next, the measures and image database used for edge detectors performance quantification are described. Ordinary users as well as authors proposing new edge detectors often use Matlab function without understanding it in details. Therefore, one chapter is devoted to some of Matlab function parameters that affect the final result. Finally, the latest trends in edge detection are listed. Picture Lena and two images from Berkeley segmentation data set (BSDS500) are used for edge detection methods comparison.en
dc.formattextcs
dc.format.extent919-929cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2018/18_04_0919_0929.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectImage processingen
dc.subjectedge detectionen
dc.subjectgradient operatoren
dc.subjectmorphological operatoren
dc.subjectfractional differentiationen
dc.subjectBerkeley segmentation data set (BSDS)en
dc.subjectNYU depth dataseten
dc.subjectMatlaben
dc.titleAbout Edge Detection in Digital Imagesen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue4cs
dc.coverage.volume27cs
dc.identifier.doi10.13164/re.2018.0919en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International license