液晶与显示2016，Vol.31Issue(10)：967-972,6.DOI:10.3788/YJYXS20163110.0967
一种多尺度灰度共生矩阵的纹理特征提取算法
Multi-scale algorithm of texture feature extraction based on gray-level co-occurrence matrix
摘要
Abstract
As an important feature,texture feature is very important in the category of Chinese paint-ing,but the majority of the existing texture extraction algorithms is based on gray-scale information. To solve the problems in Chinese painting texture extraction classification,a multi-scale,multi-color domain texture feature extraction algorithm has been proposed.This algorithm combines the advanta-ges of Contourlet transform and Gray-level Co-occurrence Matrix.In order to extract Chinese painting features by the new algorithm,the image is first transformed into HSI color space.Then,the three color components of HSI is extracted to sub-regional operation,which is to extract the texture charac-teristics of each color component.Finally,three feature vectors are integrated and the dimensionality of matrix is reduced using Principal Component Analysis.Experimental results show that compared with Gray-level Co-occurrence Matrix,the algorithm improves the precision of 7.5%,re-check rate increased by 8.7% in terms of Chinese painting classification.The experiment show that the new algo-rithm presented in this paper is better than Gray-level Co-occurrence Matrix algorithm.关键词
多尺度分析/轮廓波变换/灰度共生矩阵/国画Key words
multi-scale analysis/contourlet transform/gray-level co-occurrence matrix/Chinese paint-ing分类
信息技术与安全科学引用本文复制引用
王民,王静,王羽笙..一种多尺度灰度共生矩阵的纹理特征提取算法[J].液晶与显示,2016,31(10):967-972,6.基金项目
国家自然科学基金(No．61373112) （No．61373112）
住房和城乡建设部科学技术项目计划(No．2016-R2-045) （No．2016-R2-045）
陕西省自然科学基础研究资金(No．2014JM8343) Supported by National Natural Science Foundation of China(No．61373112) （No．2014JM8343）
Housing and Urban Ministry of Science project (No．2016-R2-045) （No．2016-R2-045）
Shaanxi Province Natural Science Basic Research funding (No．2014JM8343) （No．2014JM8343）
