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VisualRank provide ranking among images to be retrieved by measuring common visual features of the images. The similarity between images is measured by measuring similarity within extracted features like Texture, Color and Gray Histogram. Image ranked higher, when most of image features matched to features of query image. In this paper, VisualRank approach is based on k-means clustering and minimum distance findings among images is used. The results of experimental study of proposed algorithm are shown with analysis of resultant image features.
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