Comparison Of Traditional Method of HSV Histogram Equalisation with Adaptive HSVsegmentation and Kekre Transform for Content Based Image Retrieval
نویسندگان
چکیده
Content-based image retrieval system based on an efficient combination of both colors and features is explained in this paper. According to Kekre’s Transform, feature vectors are formed using a combination 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 color space quantifies the color space into different regions and thereby calculating its mean and Euclidian distance the color vector can be derived. Taking mean of the Euclidian distances of both the algorithms better accuracy of the image retrieval process can be attained. KeywordsCBIR, HSV Histogram equalization, Adaptive HSV segmentation, Kekre transform
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