Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/993
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dc.contributor.authorZuva, Tranosen_US
dc.contributor.authorOlugbara, Oludayo O.en_US
dc.contributor.authorOjo, Sunday O.en_US
dc.contributor.authorNgwira, Seleman M.en_US
dc.date.accessioned2014-05-16T08:46:00Z-
dc.date.available2014-05-16T08:46:00Z-
dc.date.issued2012-02-
dc.identifier.citationZuva, T., Olugbara, O., Ojo, S.O. and Ngwira, S.M. 2012. Kernel Density Feature Points Estimator for Content-Based Image Retrieval. The International Journal of Multimedia and Its Applications. 4(1): 103-111.en_US
dc.identifier.urihttp://hdl.handle.net/10321/993-
dc.description.abstractResearch is taking place to find effective algorithms for content-based image representation and description. There is a substantial amount of algorithms available that use visual features (color, shape, texture). Shape feature has attracted much attention from researchers that there are many shape representation and description algorithms in literature. These shape image representation and description algorithms are usually not application independent or robust, making them undesirable for generic shape description. This paper presents an object shape representation using Kernel Density Feature Points Estimator (KDFPE). In this method, the density of feature points within defined rings around the centroid of the image is obtained. The KDFPE is then applied to the vector of the image. KDFPE is invariant to translation, scale and rotation. This method of image representation shows improved retrieval rate when compared to Density Histogram Feature Points (DHFP) method. Analytic analysis is done to justify our method, which was compared with the DHFP to prove its robustness.en_US
dc.format.extent9 pen_US
dc.language.isoenen_US
dc.publisherAIRCCen_US
dc.subjectKernel Density Functionen_US
dc.subjectSimilarity, Image Representationen_US
dc.subjectSegmentationen_US
dc.subjectDensity Histogramen_US
dc.titleKernel density feature points estimator for content-based image retrievalen_US
dc.typeArticleen_US
dc.publisher.urihttp://dx.doi.org/10.5121/ijma.2012.4109en_US
dc.dut-rims.pubnumDUT-002160en_US
dc.identifier.doi10.5121/ijma.2012.4109-
item.grantfulltextopen-
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item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.openairetypeArticle-
Appears in Collections:Research Publications (Accounting and Informatics)
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