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Content-based image retrieval represents images as N-dimensional feature vectors. Similar image retrieval is computed over these high dimensional feature vectors. A sequential scan of the feature vectors for a query method is costly for a large number of images when N is high. The search time and search space can be reduced through indexing the data. In this paper we proposed a hierarchical clustering...
How to find the image we need expediently in the tremendous database is one of the most important issues in content-based image retrieval (CBIR). In this paper, we presented an image retrieval system based on image content using fuzzy logic and proposed a new concept on partition the entire database based on content self-organized. In detail, we used modified fuzzy c-means (MFCM) clustering scheme...
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