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An Effective CBIR using Texture
| International Conference and Workshop on Emerging Trends in Technology |
| Foundation of Computer Science USA |
| ICWET2012 - Number 1 |
| March 2012 |
| Authors: Asmita Deshmukh, Leena Ragha, Gargi Phadke |
| e5a9b6d8-005e-4d71-974d-7972e66c2dd0 |
Asmita Deshmukh, Leena Ragha, Gargi Phadke . An Effective CBIR using Texture. International Conference and Workshop on Emerging Trends in Technology. ICWET2012, 1 (March 2012), 4-7.
Abstract
Content Based Image Retrieval is one of the active research areas. With emerging technologies of multimedia ,communication and processing large volume of image database is used . Current approaches include the use of color, texture and shape information for CBIR. Texture feature is a kind of visual characteristic that does not rely on color and intensity and reflects the intrinsic phenomenon of images. It is total of all intrinsic surface properties. This enforces use of texture widely for image retrieval. Texture may consists of some basic primitives and may also describe the structural arrangement of a region and the relationship of the surrounding regions. Our approach uses the statistical feature using Gray Level Co-occurrence Matrix. For the texture based image retrieval Gray Level Co-occurrence Matrix can be used. A one to one matching scheme is used to compare the query and target image. Experimental results demonstrate that the propose method is very efficient and superior to some other existing method.
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