A multi-level thresholding algorithm for threshold count and values identification based on dynamic programming

dc.contributor.authorHegazy, Eslam
dc.contributor.authorGabr, Mohamed
dc.date.accessioned2025-07-30T08:11:13Z
dc.date.available2025-07-30T08:11:13Z
dc.date.issued2025
dc.description.abstract-translatedMultilevel image thresholding is a simple and efficient segmentation technique. Thresholding criteria such as Otsu and Kapur objective functions are extensively used in the literature. They are effective techniques but suffer from poor computational complexity. Thus, methods such as dynamic programming for exact optimization or metaheuristic algorithms for approximate optimization are applied to improve runtime. However, most of these algorithms take the count of thresholds as input. Hence, a novel input-less algorithm that can identify the count and values of thresholds simultaneously is proposed. The proposed method is then compared to state of the art methods to assess its efficiency and effectiveness.en
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.doihttp://www.doi.org/10.24132/JWSCG.2025-9
dc.identifier.issn1213-6972 (print)
dc.identifier.issn1213-6964 (online)
dc.identifier.urihttp://hdl.handle.net/11025/62203
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.rights© Václav Skala - UNION Agencyen
dc.rights.accessopenAccessen
dc.subjectvíceúrovňové prahovánícs
dc.subjectshlukovánícs
dc.subjectsegmentace obrazucs
dc.subjectdynamické programovánícs
dc.subjectprahování minimální chybycs
dc.subjectpřesná optimalizacecs
dc.subjectneřízená klasifikacecs
dc.subject.translatedmultilevel thresholdingen
dc.subject.translatedclusteringen
dc.subject.translatedimage segmentationen
dc.subject.translateddynamic programmingen
dc.subject.translatedminimum error thresholdingen
dc.subject.translatedexact optimizationen
dc.subject.translatedunsupervised classificationen
dc.titleA multi-level thresholding algorithm for threshold count and values identification based on dynamic programmingen
dc.typečlánekcs
dc.typearticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
local.files.count1*
local.files.size1411343*
local.has.filesyes*

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