Zobrazit minimální záznam

dc.contributor.authorHoluša, Michael
dc.contributor.authorSojka, Eduard
dc.date.accessioned2017-10-30T13:01:04Z
dc.date.available2017-10-30T13:01:04Z
dc.date.issued2017
dc.identifier.citationPattern Recognition Letters. 2017, vol. 98, p. 103-109.cs
dc.identifier.issn0167-8655
dc.identifier.issn1872-7344
dc.identifier.urihttp://hdl.handle.net/10084/120959
dc.description.abstractIn this paper, we propose a new distance called the k - max distance that is intended for graphs and images. The length of a path is defined as the sum of the k maximum arc weights along the path. The distance between two nodes is the length of the shortest path between them. We show that the k max distance is a metric. The algorithm for computing the k - max distance is presented. Certain positive properties of the k - max distance are shown, namely in the context of measuring the distances for image segmentation. The comparison with the geodesic distance, the max- arc distance, the minimum barrier distance, and the random walker technique is carried out in the segmentation of real- life images.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesPattern Recognition Letterscs
dc.relation.urihttps://doi.org/10.1016/j.patrec.2017.09.003cs
dc.rights© 2017 Elsevier B.V. All rights reserved.cs
dc.subjectdistance measuringcs
dc.subjectshortest pathcs
dc.subjectk-max distancecs
dc.subjectgeodesic distancecs
dc.subjectimage processingcs
dc.subjectimage segmentationcs
dc.titleThe k-max distance in graphs and imagescs
dc.typearticlecs
dc.identifier.doi10.1016/j.patrec.2017.09.003
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume98cs
dc.description.lastpage109cs
dc.description.firstpage103cs
dc.identifier.wos000411766300015


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Zobrazit minimální záznam