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。
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。
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。
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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