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Content-Based Image Retrieval aims at developing techniques that support effective searching and browsing of large image repositories based on image features. The current Content-Based Image Retrieval suffer from the semantic gap. it often leads to distraction in the search. To overcome these disadvantages, Combine the theory of high dimensional information property, we propose different dimensional space’s vector angel cosine algorithm based on high dimensional information theory. The experimental results demonstrate the performance of the proposed algorithm.

Interactive Image Contents Search Based on High Dimensional Information Theory