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灰度共生矩阵检索纹理图像的算法研究
引用本文:苑丽红,孙爽滋,付丽.灰度共生矩阵检索纹理图像的算法研究[J].计算机科学,2009,36(11):300-303.
作者姓名:苑丽红  孙爽滋  付丽
作者单位:长春理工大学计算机科学技术学院,长春,130022
摘    要:图像的特征提取和匹配是基于内容的图像检索技术的基础.针对典型纹理图像的检索问题,给出了共生矩阵特征统计量的合理提取方法.在此基础上,结合特征匹配技术实现了基于共生矩阵的纹理图像检索系统.测试了不同度量函数以及不同的特征统计组合对检索结果的影响.研究表明,提取共生矩阵的四参数,用加权街区距离进行图像匹配,可获得相对较好的检索效果.

关 键 词:图像检索  特征提取  灰度共生矩阵
收稿时间:2009/1/10 0:00:00
修稿时间:2009/9/10 0:00:00

Study on Algorithm of Texture Image Retrival by Gray Level Co-occurrence Matrix
YUAN Li-hong,SUN Shuang-zi,FU Li.Study on Algorithm of Texture Image Retrival by Gray Level Co-occurrence Matrix[J].Computer Science,2009,36(11):300-303.
Authors:YUAN Li-hong  SUN Shuang-zi  FU Li
Affiliation:(School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China)
Abstract:Image's feature extraction and matching is essential for content based image retrieval. Io retrieve texture image better, this paper discussed the Rational method for extract features of texture image by gray level co-occurrence matrix. Then combined with similarity measures, the basic system based on LLCM was developed. Different measure funcdons and different combination of statistics were used to analyze their effect on retrieval. I}he result indicates that better retrieval performance is achieved by extracting four parameters from GLOM and measuring them with weighted block distance.
Keywords:Image retrieval  Feature extraction  Gray level co-occurrence matrix
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