Interpretation of Fuzzy Logic For Texture Queries in CBIR
| dc.contributor.author | Kulkarni, S. | en_US |
| dc.contributor.editor | Peter Hall and Philip Willis | en_US |
| dc.date.accessioned | 2016-02-09T10:27:06Z | |
| dc.date.available | 2016-02-09T10:27:06Z | |
| dc.date.issued | 2003 | en_US |
| dc.description.abstract | This 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.sectionheaders | Poster Session 2 | en_US |
| dc.description.seriesinformation | Vision, Video, and Graphics (VVG) 2003 | en_US |
| dc.identifier.doi | 10.2312/vvg.20031024 | en_US |
| dc.identifier.isbn | 3-905673-54-1 | en_US |
| dc.identifier.pages | S. Kulkarni-Fuzzy logic, Texture features, Image retrieval, Feature extraction | en_US |
| dc.identifier.uri | https://doi.org/10.2312/vvg.20031024 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Fuzzy logic | en_US |
| dc.subject | Texture features | en_US |
| dc.subject | Image retrieval | en_US |
| dc.subject | Feature extraction | en_US |
| dc.title | Interpretation of Fuzzy Logic For Texture Queries in CBIR | en_US |
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