北京生物医学工程2018，Vol.37Issue(2)：157-163,7.DOI:10.3969/j.issn.1002-3208.2018.02.008
一种改进的中医舌苔厚度自动描述方法
An improved automatic description method of tongue coating thickness in Chinese medicine
摘要
Abstract
Objective The objectification of tongue diagnosis is one of the important contents of modernization of Chinese medicine,and the quantitative description of tongue coating is its important indexes.The thickness of tongue coating in traditional classification is qualitatively divided into two categories:thick coating and thin coating,yet there is a lack of quantitative description.A method combining gray-level co-occurrence matrix(GLCM)and wavelet texture feature extraction is proposed in this paper.Methods Firstly,the orthogonal wavelet of Daubechies2 is adopted to decompose the tongue image into primary wavelet,and we calculate the average and variance of the three detail subgraphs as features.Secondly,GLCM is used to extract the contrast,inverse gap,energy and correlation of 0°,45°,90° the three directions in approximate subgraph.On this basis,classifier of support vector machine(SVM)is trained to analyze the tongue images qualitatively based on that features.At the same time,the support vector regression(SVR)model for quantitative analysis of tongue coating thickness is established. Results A total of 200 cases of tongue samples are taken,of which 100 cases are thin fur and 100 cases are thick fur,60 cases of thin fur and 60 cases of thick fur samples are selected to train the classifier, and 80 samples are test samples.Conclusions The experimental results show that compared with the traditional wavelet texture feature extraction method,the method proposed in this paper can improve the effect of classification of tongue coating thickness.关键词
舌苔/薄厚/纹理特征提取/定性分析/定量分析Key words
tongue coating/thickness/texture feature extraction/qualitative analysis/quantitative analysis分类
医药卫生引用本文复制引用
刘斌,胡广芹,张新峰,冯利,李泉旺..一种改进的中医舌苔厚度自动描述方法[J].北京生物医学工程,2018,37(2):157-163,7.基金项目
北京市属高等学校高层次人才引进与培养计划项目(CIT&TCD201504018)资助 （CIT&TCD201504018）
