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- W2462034293 abstract "The content based image retrieval method greatly assists in retrieving medical images close to the query image from a large database basing on their visual features. This paper presents an effective approach in which the region of the object is extracted with the help of multiple features ignoring the background of the object by employing edge following segmentation method followed by extracting texture and shape characteristics of the images. The former is extracted with the help of Steerable filter at different orientations and radial Chebyshev moments are used for extracting the later. Initially the images similar to the query image are extracted from a large group of medical images. Then the search is by accelerating the retrieval process with the help of Support Vector Machine (SVM) classifier. The performance of the retrieval system is enhanced by adapting the subjective feedback method. The experimental results show that the proposed region based multiple features and integrated with classifier and subjective feedback method yields better results than classical retrieval systems." @default.
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- W2462034293 date "2016-01-01" @default.
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- W2462034293 title "Integrated Multiple Features for Tumor Image Retrieval Using Classifier and Feedback Methods" @default.
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- W2462034293 doi "https://doi.org/10.1016/j.procs.2016.05.200" @default.
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