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Proceedings of 2009 International Symposium on Computer Science and Computational Technology (ISCSCT 2009)

Huangshan, China, December 26-28, 2009

Editors: Fei Yu, Guangxue Yue, Jian Shu, Yun Liu

AP Catalog Number: AP-PROC-CS-09CN005

ISBN: 978-952-5726-07-7 (Print), 978-952-5726-08-4 (CD-ROM)

Page(s): 274-277

Application Research of k-means Clustering Algorithm in Image Retrieval System

††††††† Hong Liu and Xiaohong Yu

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In image retrieval algorithms, retrieval is according to feature similarities with respect to the query, ignoring the similarities among images in database. To use the feature similarities information, this paper presents an application of k-means clustering algorithm to image retrieval system. Combining the low-level visual features and high-level concepts, the proposed approach fully explores the similarities among images in database, using such clustering algorithm and optimizes the relevance results from traditional image retrieval system by firstly clustering the similar images in the images database to improve the efficiency of images retrieval system. The results of experiments on the testing images show that the proposed approach can greatly improve the efficiency and performances of image retrieval, as well as the convergence to userís retrieval concept.

Index Terms

image retrieval, k-means cluster algorithm, feature extraction

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