Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/80642
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dc.contributor.authorHerdiyeni, Yeni-
dc.contributor.authorPebuardi, Rizki-
dc.contributor.authorBuono, Agus-
dc.date.accessioned2016-05-21T03:45:23Z-
dc.date.available2016-05-21T03:45:23Z-
dc.date.issued2009-
dc.identifier.isbn978-979-1344-67-8-
dc.identifier.urihttp://repository.ipb.ac.id/handle/123456789/80642-
dc.description.abstract,This paper proposed bayesian Network approach for image similarity measurement based on color , shape and texture . Bayesian network model can derermine dominant information of an imagec using orcurrence probability of image's characteristics. This probabililyty is usedd t0 measure image similarity Performance of the sysrem is determined using recall and preccision. Based on experiment, Bayesian network model can improve performance of image retrieval system. Experiment result ,showed that the average precision gain up of using Bayesian network model is about 8.28%. The average precision of using Bayesian network model is better than using color, shape, or texture information individually.id
dc.language.isoenid
dc.publisherBogor Agricultural University (IPB)id
dc.publisherBogor Agricultural University (IPB)id
dc.titleA Bayesian Network Approach for lmage Similarityid
dc.typeArticleid
dc.subject.keywordBayesian network,id
dc.subject.keywordhistogram-162id
dc.subject.keywordedge direction histogram,id
dc.subject.keywordco-occurrence matriksid
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