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Comparision Of Traditional Method of Histogram Equalisation with HSV and Kekre Transform for Content Based Image Retrieval

Author(s): Ms. Venu Shah, | Ms. Archana Choudhary, | Prof. Kavita Tewari

Journal: International Journal on Computer Science and Engineering
ISSN 0975-3397

Volume: 3;
Issue: 7;
Start page: 2712;
Date: 2011;
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Keywords: CBIR | Histogram equalisation | HSV segmentation

Content-based image retrieval system based on an efficient combination of both colours and features is explained in this paper. According to Kekre’s Transform, feature vectors are formed using acombination of row mean and column mean of both query as well as database images, to measure the extent of similarity using Euclidian distance. Similarly, HSV colour space quantifies the colour space intodifferent regions and thereby calculating its mean and Euclidian distance the colour vector can be derived. Taking mean of the Euclidian distances of both the algorithms better accuracy of the image retrieval process can be attained.
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