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dc.contributor.authorŽunić, Anastaziaen_US
dc.date.accessioned2022-12-09T14:04:43Z-
dc.date.available2022-12-09T14:04:43Z-
dc.date.issued2018-
dc.identifier.issn0020-0190-
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/4934-
dc.description.abstractShape diameter, defined as the longest distance between two shape points, is a natural and dissent shape characteristics. In this paper we show how the shape diameter can be utilized to define two quantities, herein named the elongation measures. Both measures have a discriminative capacity and, as such, can be used to distinguish among the objects presented on digital images. The first elongation measure is based on comparison of the shape diameter and shape area. The second one is based on the relationship between the shape diameter and shape perimeter. The basic desirable properties of the new measures are given. A number of simple examples are given in order to illustrate the behavior of the new measures.en_US
dc.publisherElsevieren_US
dc.relation.ispartofInformation Processing Lettersen_US
dc.subjectComputational geometry | Image processing | Pattern recognition | Shape analysisen_US
dc.titleShape diameter for object analysisen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.ipl.2018.03.012-
dc.identifier.scopus2-s2.0-85045570053-
dc.relation.firstpage76-
dc.relation.lastpage79-
dc.relation.volume136-
dc.description.rankM23-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.orcid0000-0001-5222-1268-
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