Interpretation of Fuzzy Logic For Texture Queries in CBIR

dc.contributor.authorKulkarni, S.en_US
dc.contributor.editorPeter Hall and Philip Willisen_US
dc.date.accessioned2016-02-09T10:27:06Z
dc.date.available2016-02-09T10:27:06Z
dc.date.issued2003en_US
dc.description.abstractThis paper presents a novel fuzzy logic based approach for the interpretation of texture queries. Tamura feature extraction technique is used to extract each texture feature of an image in the database. A term set on each Tamura feature is generated by a fuzzy clustering algorithm to pose a query in terms of natural language. The query can be expressed as a logic combination of natural language terms and tamura feature values. The performance of the technique was evaluated on Brodatz texture benchmark database. Experimental results show that the proposed technique is effective and the retrieved images indicate that those images are suitable for the specific queries.en_US
dc.description.sectionheadersPoster Session 2en_US
dc.description.seriesinformationVision, Video, and Graphics (VVG) 2003en_US
dc.identifier.doi10.2312/vvg.20031024en_US
dc.identifier.isbn3-905673-54-1en_US
dc.identifier.pagesS. Kulkarni-Fuzzy logic, Texture features, Image retrieval, Feature extractionen_US
dc.identifier.urihttps://doi.org/10.2312/vvg.20031024en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectFuzzy logicen_US
dc.subjectTexture featuresen_US
dc.subjectImage retrievalen_US
dc.subjectFeature extractionen_US
dc.titleInterpretation of Fuzzy Logic For Texture Queries in CBIRen_US
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