An Optimized Image Retrieval Method based on Hierarchal Clustering and Genetic Algorithm

被引：0
|
作者：
Huang Min [1 ]
Sun Bo [2 ]
Xi Jianqing [1 ]
机构：
[1] SCUT, Sch Software Engn, Guangzhou 510006, Guangdong, Peoples R China
[2] GdUFS, Res Ctr Int Trade Econ, Guangzhou 510420, Guangdong, Peoples R China
来源：
2009 INTERNATIONAL FORUM ON INFORMATION TECHNOLOGY AND APPLICATIONS, VOL 1, PROCEEDINGS | 2009年
关键词：
Image retrieval; Search engine; Multi-Optimization; Relevance feed-back; Hierarchal clustering; Genetic Algorithm;
D O I：
10.1109/IFITA.2009.429
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Image search on web is very familiar to various users, and improving the efficiency and accuracy of image search has become more and more a hotpot in this research field For different commercial image engines use different retrieval techniques respectively, the coverage area and accuracy of each individual search engine await development. An imp raved method based on multi-optimization techniques of image retrieval is presented in the paper. On the base of relevance-feedback principle, the method does some work of the vectorization and weights adjusting to the images generated by commercial image engines, and then adopts hierarchal clustering and genetic algorithm techniques to optimize the results further. Finally, by developing a prototype of image retrieval engine based on the method presented and doing some tests, the advancing in accuracy of image retrievals of the method has been proved.
引用
收藏
页码：747 / +
页数：2
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