摘要
针对利用颜色直方图进行图像检索时存在的问题,提出了一种基于空间分布特征的图像检索算法。首先将图像分解为8个位平面,并采用其中对表征图像结构特征有意义的4个位平面的分布特征对图像内容进行描述,同时,为避免图像中像素灰度值的微小变化对位平面的影响,又提出采用位平面的格林码表示方法。考虑到位平面之间的相关性,设计了权值矩阵,采用马氏距离进行相似性度量。实验结果表明,该算法利用位平面分解的方法来提取颜色的空间分布信息,可避免颜色量化引起的误检问题,而且提取的特征矢量维数较低,具有较高的检索率。
Based on the analysis of the problems in image retrieval using color histograms, this paper proposes a novel spatial distribution-based method for image retrieval. The method firstly divides the image into eight bit-planes and introduces the Gray code to avoid the effect of the variation of their intensity values. Then, a feature vector, including the distribution information of the first four significant planes, is presented as an index for image retrieval. It combines with the new designed correlation-weighted matrix, and adopts the Mahalanobis distance as a measure rule. The comparisons with other related descriptors were conducted and the experimental results showed that the proposed method provided more significantly results than the traditional ones.
出处
《高技术通讯》
EI
CAS
CSCD
北大核心
2009年第4期382-385,共4页
Chinese High Technology Letters
基金
南京邮电大学江苏省重点实验室开放基金(ZK208002)
河南省教育厅自然科学基础研究基金(2008B520015
2009B520013)
河南理工大学博士基金(B050901
B2008-61
B2002-91)资助项目
关键词
基于内容的图像检索
位平面
格林码
空间分布信息
content-based image retrieval, bit-planes, Gray-code, spatial distribution information