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http://repository.ipb.ac.id/handle/123456789/80642
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Herdiyeni, Yeni | - |
dc.contributor.author | Pebuardi, Rizki | - |
dc.contributor.author | Buono, Agus | - |
dc.date.accessioned | 2016-05-21T03:45:23Z | - |
dc.date.available | 2016-05-21T03:45:23Z | - |
dc.date.issued | 2009 | - |
dc.identifier.isbn | 978-979-1344-67-8 | - |
dc.identifier.uri | http://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.iso | en | id |
dc.publisher | Bogor Agricultural University (IPB) | id |
dc.publisher | Bogor Agricultural University (IPB) | id |
dc.title | A Bayesian Network Approach for lmage Similarity | id |
dc.type | Article | id |
dc.subject.keyword | Bayesian network, | id |
dc.subject.keyword | histogram-162 | id |
dc.subject.keyword | edge direction histogram, | id |
dc.subject.keyword | co-occurrence matriks | id |
Appears in Collections: | Computer Science |
Files in This Item:
File | Size | Format | |
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Prosid AB8.pdf | 3.01 MB | Adobe PDF | View/Open |
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