FORMAL DEFINITION AND ENTROPY CALCULATION OF HIERARCHICAL ATTRIBUTED RANDOM GRAPH

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dc.contributor.authorSEONG, DSko
dc.contributor.authorKIM, HSko
dc.contributor.authorPark, Kyu Hoko
dc.date.accessioned2013-02-25T23:41:37Z-
dc.date.available2013-02-25T23:41:37Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued1992-08-
dc.identifier.citationPATTERN RECOGNITION LETTERS, v.13, no.8, pp.545 - 555-
dc.identifier.issn0167-8655-
dc.identifier.urihttp://hdl.handle.net/10203/66069-
dc.description.abstractFor the representation of a complex object, the object is decomposed into several parts, and it is described by these decomposed parts and their relations. In general, the parts can be the primitive elements that can not be decomposed further, or still can be decomposed into their subparts. Therefore, the hierarchical description method is very natural and the hierarchical description is represented by a hicrarchical graph whose vertices represent either primitive elements or graphs. These graphs also have vertices which contain primitive elements or graphs. When some uncertainty exists in the hierarchical description of a complex object either due to noise or minor deformation, a probabilistic description of the object ensemble is necessary. For this purpose, in this paper, we formally define the hierarchical attributed random graph and derive the equations fo the entropy calculation of the hierarchical random graph.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE BV-
dc.subjectRECOGNITION-
dc.titleFORMAL DEFINITION AND ENTROPY CALCULATION OF HIERARCHICAL ATTRIBUTED RANDOM GRAPH-
dc.typeArticle-
dc.identifier.wosidA1992JJ32400002-
dc.identifier.scopusid2-s2.0-38249010537-
dc.type.rimsART-
dc.citation.volume13-
dc.citation.issue8-
dc.citation.beginningpage545-
dc.citation.endingpage555-
dc.citation.publicationnamePATTERN RECOGNITION LETTERS-
dc.identifier.doi10.1016/0167-8655(92)90089-I-
dc.contributor.localauthorPark, Kyu Ho-
dc.contributor.nonIdAuthorSEONG, DS-
dc.contributor.nonIdAuthorKIM, HS-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorHIERARCHICAL ATTRIBUTED RANDOM GRAPH-
dc.subject.keywordAuthorHIERARCHICAL DESCRIPTION-
dc.subject.keywordAuthorENTROPY-
dc.subject.keywordPlusRECOGNITION-
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