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There is a gap between low-level descriptions of image content and the semantic understanding of users to query image databases in the content-based image retrieval. In this paper, the authors put forward a method of classifying image regions hierarchically using their semantics and that resembles peoples' perception more than using low-level features. The experiments show, the better precision of semantic classification justifies the feasibility of their method. It uses in image retrieval field further and get better index effect.
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