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浙江大学学报(工学版)
J4  2010, Vol. 44 Issue (9): 1654-1658    DOI: 10.3785/j.issn.1008-973X.2010.09.004
自动化技术、计算机技术     
基于保局映射的图像纹理聚类
幸锐1,张引1,张三元1,竺乐庆2
1. 浙江大学 计算机科学与技术学院,浙江 杭州 310027；
2. 浙江工商大学 计算机与信息工程学院,浙江 杭州 310018
Image texture clustering based on locality preserving projection
XING Rui1, ZHANG Yin1, ZHANG San-yuan1, ZHU Le-qing2
1. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China;
2. College of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018,China
 全文: PDF 
摘要：

为了解决图像检索中的聚类问题,提出一种改进的图像纹理聚类算法.在纹理特征提取阶段,采用双树复小波对图像进行分解,然后对每个高频段提取直方图签名作为纹理特征;在聚类阶段,根据数据分布的密度来动态地计算数据点的邻接矩阵,再采用保局映射进行降维,对降维后的数据进行kmeans聚类.通过采用直方图签名的方式能有效地表示图像纹理在各个方向上特征信息,同时根据数据密度构建的邻接矩阵,能够和保局映射一起更有效地发掘数据之间的局部相关性.实验表明：相对于传统方法,该算法具有更高的聚类正确性.
关键词： 双树复小波;  保局映射;  纹理签名;  降维    
Abstract:

An improved image texture clustering method was proposed to solve the clustering problem in image retrieval. In feature extraction stage, dualtree complex wavelet transform（DTCWT）is applied to decompose image into tens of subbands. For those high frequency subbands, histogram signatures are generated as one of the texture features. In clustering stage, the distances between the data points are computed adaptively according to the data distribution density. Locality preserving projection is then employed on the distances to reduce the dimensionality of the data space. kmeans is used to cluster the data in the lower dimensionality space. Histogram signature can represent image texture well in multiple directions of the DTCWT decomposition. Moreover, the distance matrix built on data density can detect dataset locality effectively in combination with locality preserving projection. The experimental results  show that the proposed method outperforms the traditional methods．
Key words: DT-CWT    locality preserving projection    texture signature    dimension reduction
出版日期: 2010-10-10
:  TP 391  
基金资助:

国家“863”高技术研究发展计划资助项目（2009CB320800）；浙江省自然科学基金资助项目（Y1090597）
通讯作者: 张引，女，副教授.     E-mail: yinzh@cs.zju.edu.cn
作者简介: 幸锐（1978-），男，浙江富阳人，博士生，主要从事图像处理和模式识别的研究. E-mail:xingrui@zju.edu.cn
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引用本文:

幸锐, 张引, 张三元, 竺乐庆. 基于保局映射的图像纹理聚类[J]. J4, 2010, 44(9): 1654-1658.

NIE Dui, ZHANG Yin, ZHANG San-Yuan, DU Le-Qiang. Image texture clustering based on locality preserving projection. J4, 2010, 44(9): 1654-1658.

链接本文:

http://www.zjujournals.com/xueshu/eng/CN/10.3785/j.issn.1008-973X.2010.09.004    或    http://www.zjujournals.com/xueshu/eng/CN/Y2010/V44/I9/1654

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