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dc.contributor.authorDeng, Daen_NZ
dc.date.available2011-04-07T03:06:13Z
dc.date.copyright2005-12en_NZ
dc.identifier.citationDeng, D. (2005). Content-based image collection summarization and comparison using self-organizing maps (Information Science Discussion Papers Series No. 2005/11). University of Otago. Retrieved from http://hdl.handle.net/10523/1038en
dc.identifier.urihttp://hdl.handle.net/10523/1038
dc.description.abstractProgresses made on content-based image retrieval has reactivated the research on image analysis and similarity-based approaches have been investigated to assess the similarity between images. In this paper, the content-based approach is extended towards the problem of image collection summarization and comparison. For these purposes we propose to carry out clustering analysis on visual features using self-organizing maps, and then evaluate their similarity using a few dissimilarity measures implemented on the feature maps. The effectiveness of these dissimilarity measures is then examined with an empirical study.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherUniversity of Otagoen_NZ
dc.relation.ispartofseriesInformation Science Discussion Papers Seriesen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleContent-based image collection summarization and comparison using self-organizing mapsen_NZ
dc.typeDiscussion Paperen_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages20en_NZ
otago.date.accession2005-12-05en_NZ
otago.schoolInformation Scienceen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints147en_NZ
otago.school.eprintsKnowledge, Intelligence & Web Informatics Laboratoryen_NZ
otago.school.eprintsInformation Scienceen_NZ
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otago.relation.number2005/11en_NZ
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