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基于颜色特征利用色矩与BTC法进行影像聚类
引用本文:丁启伟,戴晨光,赵博. 基于颜色特征利用色矩与BTC法进行影像聚类[J]. 测绘与空间地理信息, 2011, 34(3): 162-164,167
作者姓名:丁启伟  戴晨光  赵博
作者单位:信息工程大学测绘学院,河南郑州,450052;65014部队,辽宁沈阳,110027
摘    要:影像聚类是一种对影像数据进行分组的方法,在基于内容的影像检索中,如果能够利用较低层次的可视特征进行高效的影像聚类,将会大大提高影像检索的精度.文章分别利用色矩法与分块截短编码(BTC)方法提取影像颜色特征,然后采用K均值聚类算法来对两种方法进行聚类分析.实验结果表明,分块截短编码(BTC)方法的聚类精度优于色矩法.

关 键 词:影像特征  聚类  色矩  BTC

Image Clustering Using Color Moments and BTC Approach Based on Color Features
DING Qi-wei,DAI Chen-guang,ZHAO Bo. Image Clustering Using Color Moments and BTC Approach Based on Color Features[J]. Geomatics & Spatial Information Technology, 2011, 34(3): 162-164,167
Authors:DING Qi-wei  DAI Chen-guang  ZHAO Bo
Affiliation:DING Qi-wei1,DAI Chen-guang1,ZHAO Bo2(1.Institute of Surveying and Mapping,Information Engineering University,Zhengzhou 450052,China,2.65014 Troops,Shenyang 110027,China)
Abstract:Image clustering is an approach to group a set of image data into different meaningful categories.The precision of the image retrieving will be much more improved in the content-based image retrieval if using the low-level visual features to cluster the images efficiently.In this paper,color moment and Block Truncation Coding(BTC) were used to extract color features,and K-Means clustering algorithm was conducted to cluster the image data based on the features.The experiment showed that the method of BTC is ...
Keywords:image features  clustering  color moments  BTC  
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