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In this research, we have proposed semantic based image retrieval system to retrieve set of relevant images for the given query image from the Web. We have used global color space model and Dense SIFT feature extraction technique to generate visual dictionary using proposed quantization algorithm. The images are transformed into set of features. These(More)
Image retrieval system is an active area to propose a new approach to retrieve images from the large image database. In this concerned, we proposed an algorithm to represent images using divisive based and partitioned based clustering approaches. The HSV color component and Haar wavelet transform is used to extract image features. These features are taken(More)
In this paper we propose a novel methodology for Web Image retrieval system that takes an image as the input query and retrieves images based on image content. Content Based Image Retrieval is an approach for retrieving semantically-relevant images from an image store based on algorithmically-derived image features. We propose an algorithm to represent(More)
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