计算机科学 ›› 2015, Vol. 42 ›› Issue (2): 311-315.doi: 10.11896/j.issn.1002-137X.2015.02.066
张永库,李云峰,孙劲光
ZHANG Yong-ku, LI Yun-feng and SUN Jing-guang
摘要： 为了提高图像检索的速度和准确率,通过分析各种聚类算法在图像检索中的缺点,提出了一种新的划分聚类的图像检索方法。首先,在对HSV模型非均匀量化的基础上,利用改进的颜色聚合向量方法提取图像的颜色特征；然后找到符合条件的特征向量作为初始聚类中心,利用分散度与贡献度进行聚类并建立特征索引库；最后根据查询图像的相似度进行检索和排序。实验结果表明,所提算法的查准率和查全率比其它算法均有较大提高。
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