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基于空间分布差异度的分块彩色图像检索方法
引用本文:陈骍,檀结庆.基于空间分布差异度的分块彩色图像检索方法[J].计算机应用,2012,32(6):1539-1543.
作者姓名:陈骍  檀结庆
作者单位:1. 合肥工业大学 计算机与信息学院,合肥 2300092. 中国西昌卫星发射中心 指挥控制站,四川 西昌 615621
基金项目:国家自然科学基金-广东联合基金重点项目,国家自然科学基金资助项目,安徽省自然科学基金资助项目,安徽省教育厅科技创新团队基金资助项目
摘    要:传统的基于颜色直方图的彩色图像检索方法具有计算简单和尺度变化不敏感的优点,但传统的方法普遍存在丢失图像空间信息和特征维数较高的缺点。为克服上述缺陷,提出了一种基于空间分布差异度的分块颜色直方图图像检索新方法。该算法首先将图像进行划分,并计算图像各子块间的相似度;然后,对分块的图像进行空间分布差异度的计算,并由此确定各分块的权值系数;最后,对各子块的相似度进行加权累加从而得到整幅图像的相似度。实验表明,该算法能克服传统方法的弊端,并具有较好的平均查找性能。

关 键 词:基于内容的图像检索    空间分布    差异度    颜色直方图    权值
收稿时间:2011-11-30
修稿时间:2012-02-04

Color block-histogram image retrieval based on difference degree of spatial distribution
CHEN Xing , TAN Jie-qing.Color block-histogram image retrieval based on difference degree of spatial distribution[J].journal of Computer Applications,2012,32(6):1539-1543.
Authors:CHEN Xing  TAN Jie-qing
Affiliation:1. College of Computer and Information, Hefei University of Technology, Hefei Anhui 230009,China2. Station of Command and Control, Xichang Satellite Launch Center, Xichang Sichuan 615621,China
Abstract:Traditional method of color image retrieval based on color histogram is of simple calculation and its scale is not sensitive to change.But the traditional approach also has some disadvantages: the spatial information of image is lost and the image feature dimension is high.In order to overcome the defects,this paper presented a new method of image retrieval,based on the difference degree of spatial distribution.First,the image was split into blocks and the similarity of these blocks was formed;second,the difference degree of spatial distribution was calculated,and then the weight values of each partition were defined.Finally,the similarity in different branch module will be accumulated by weight to get the whole image similarity.The experimental results show that this algorithm can overcome the disadvantages of the traditional method,and has better retrieval performance.
Keywords:Content Based Image Retrieval(CBIR)  spatial distribution  difference degree  color histogram  weight
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