This paper proposes an indexing algorithm of clustering which supports QBE image retrieval for large image databases.

本文提出了一种有效的支持海量图像数据库Q BE查询的聚类索引算法。

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Based on dimension reduction, it puts forward a new indexing structure to improve the performance of content-based retrieval of large image databases.

在降维的基础上，建立了一个新的索引机制，并以此加速大规模图像库的基于内容检索的进程。

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As the volume of image database grows, it is urged to work over high effective index technique to support fast similarity search in very large databases.

图像数据库容量的增长，迫切需要研究高效的索引技术来支持快速相似性检索的要求。

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