CAJ | 학술논문

目的：建立基于切面图像纹理特征参数的辨识模型，探讨中药饮片自动识别的可行性。方法：基于中药饮片切面图像的灰度共生矩阵和灰度梯度共生矩阵，选取18种中药材不同样本图像的26个纹理特征参数，分别建立训练集和测试集。利用最小协方差行列式 MCD方法对训练集进行离群值剔除处理。采用朴素贝叶斯及BP神经网络2种建模方法和十折交叉验证，建立18种中药材的判别模型。结果：在提取的26个纹理特征参数的基础上，利用MCD方法剔除训练集的离群值后，用BP神经网络建立的判别模型判正率达到90%，说明效能良好。结论：将建立的辨识模型用于中药饮片的自动识别具有可行性，为中药直观鉴别的定量化、科学化以及客观化提供了一套新的技术手段。
목적：건립기우절면도상문리특정삼수적변식모형，탐토중약음편자동식별적가행성。방법：기우중약음편절면도상적회도공생구진화회도제도공생구진，선취18충중약재불동양본도상적26개문리특정삼수，분별건립훈련집화측시집。이용최소협방차행렬식 MCD방법대훈련집진행리군치척제처리。채용박소패협사급BP신경망락2충건모방법화십절교차험증，건립18충중약재적판별모형。결과：재제취적26개문리특정삼수적기출상，이용MCD방법척제훈련집적리군치후，용BP신경망락건립적판별모형판정솔체도90%，설명효능량호。결론：장건립적변식모형용우중약음편적자동식별구유가행성，위중약직관감별적정양화、과학화이급객관화제공료일투신적기술수단。
This study was aimed to establish the classification method of Chinese herbal medicine based on feature parameters extracted from images of herbal transverse section, in order to explore the feasibility of automatic identi-fication method of herbal medicine. The extracted 26 parameters of 18 herbal medicine images by gray-level co-oc-currence matrix and grayscale gradient matrix were used as the basic data set. And the minimum covariance determi-nant (MCD) was used to delete the outliers. A total of 18 identification models were established using the native Bayes method and BP neural network methods. The results showed that the average correct rates of models were 90%. It was concluded the feasibility of using these models in the establishment of the automatic identification method of herbal medicines. It provided new technologies for the quantitative, scientific and objective identification of Chinese herbal medicine.