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In this paper we proposed, a novel framework to assist and automate the diagnosis of diseases from computer-based image analysis method using Content-based image retrieval (CBIR). CBIR is the process of retrieving related images from large database collections by using low level image features such as color, texture and shape etc. we have used fuzzy texton and discrete shearlet transform to extract texture and shape features. The aim is to support decision making by retrieving and displaying relevant past cases visually similar to the one under examination with relevance feedback using Support Vector Machines.
Sudhakar Putheti. 2015. \u201cSupervised Content based Image Retrieval using Fuzzy Texton and Shearlet Transform\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 15 (GJCST Volume 15 Issue F1): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 103
Country: India
Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision
Authors: Sudhakar Putheti, Mohan Krishna kotha,Srinivasa Reddy Edara (PhD/Dr. count: 0)
View Count (all-time): 290
Total Views (Real + Logic): 7982
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Publish Date: 2015 06, Thu
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In this paper we proposed, a novel framework to assist and automate the diagnosis of diseases from computer-based image analysis method using Content-based image retrieval (CBIR). CBIR is the process of retrieving related images from large database collections by using low level image features such as color, texture and shape etc. we have used fuzzy texton and discrete shearlet transform to extract texture and shape features. The aim is to support decision making by retrieving and displaying relevant past cases visually similar to the one under examination with relevance feedback using Support Vector Machines.
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