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Selection of the Proper Compact Composite Descriptor for Improving Content based Image Retrieval

dc.contributor.authorChatzichristofis, Savvas A.
dc.contributor.authorBoutalis, Yiannis
dc.contributor.authorLux, Mathias
dc.date.accessioned2017-10-24T11:04:56Z
dc.date.available2017-10-24T11:04:56Z
dc.date.issued2009
dc.identifier.urihttp://hdl.handle.net/11728/10149
dc.description.abstractCompact Composite Descriptors (CCD) are global image features capturing both, color and texture characteristics, at the same time in a very compact representation. In this paper we propose a combination of two recently introduced CCDs (CEDD and FCTH) into a Joint Composite Descriptor (JCD). We further present a method for descriptor selection to approach the best ANMRR that would result from CEDD and FCTH. With our approach the most appropriate descriptor in terms of maximization of information content can be found on a per image basis without knowledge of the data set as a whole. Experiments conducted on three known benchmarking image databases demonstrate the effectiveness of the proposed technique.en_UK
dc.language.isoenen_UK
dc.publisherACTA Press, Canadaen_UK
dc.relation.ispartofseriesProceedings of the 6th IASTED International Conference;Signal Processing, Pattern Recognition and Applications (SPPRA 2009), February 17-19, 2009 Innsbruck, Austria
dc.rights© Copyright 2017 ACTA Pressen_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.source.urihttps://www.actapress.com/Abstract.aspx?paperId=38597en_UK
dc.subjectResearch Subject Categories::TECHNOLOGYen_UK
dc.subjectCompact Composite Descriptorsen_UK
dc.subjectCBIRen_UK
dc.subjectSelection of the proper descriptoren_UK
dc.subjectFuzzy techniquesen_UK
dc.titleSelection of the Proper Compact Composite Descriptor for Improving Content based Image Retrievalen_UK
dc.typeWorking Paperen_UK


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