發(fā)布時間：2018-05-29 05:29

  本文選題：Matlab + 特征定量��； 參考：《廣州中醫(yī)藥大學(xué)》2017年碩士論文

【摘要】：目的:(1)結(jié)合計算機(jī)圖像處理技術(shù)及攝像技術(shù),定量測定不同產(chǎn)地的麥冬、玉竹、太子參的外觀性狀特征以及各種組織形態(tài)特征,同時構(gòu)建所選藥材不同產(chǎn)地的神經(jīng)網(wǎng)絡(luò)識別模型。利用圖像處理軟件,探究相應(yīng)的算法,盡可能實現(xiàn)自動化、批量化操作,(2)對不同產(chǎn)地藥材的總皂苷類成分進(jìn)行組織化學(xué)定位和吸光度測定、建立組織特征參數(shù)與化學(xué)成分之間的相關(guān)性。為中藥的鑒定及其質(zhì)量標(biāo)準(zhǔn)控制研究提供一種新思路、新方法。方法:從所購得藥材中隨機(jī)抽取所需數(shù)量的樣本,將所得樣本置于白紙上,利用數(shù)碼攝像設(shè)備攝取其宏觀圖片。而后,將已攝取的圖片的藥材按聚乙二醇包埋法制備顯微裝片,利用電子目鏡攝像頭在顯微鏡下無間隔地移動視野,且相鄰視野間保持一定的重復(fù)區(qū)域,不間斷攝取藥材顯微圖像的全貌。利用Matlab平臺編寫程序結(jié)合Image Pro Plus圖像測定軟件對顯微圖像以及前面所攝取的外觀圖像進(jìn)行處理,測量不同藥材對應(yīng)的宏觀及顯微特征參數(shù)。收集實驗所需的各項參數(shù)并進(jìn)行統(tǒng)計分析。對比同一藥材不同產(chǎn)地或者是不同部位的特征差異,并由此構(gòu)建出識別該類藥材的特征向量。利用Matlab2014a自帶的模式識別工具箱對藥材的識別分析,同時采用相關(guān)分析對所選藥材的特征與化學(xué)成分含量做統(tǒng)計分析結(jié)果:(1)實現(xiàn)了對麥冬、玉竹、太子參三種藥材的形狀、顏色、大小、表面紋理特征以及各組織特征的定量描述。(2)建立了適用于大量顯微圖像拼接的方法。(3)構(gòu)建了識別麥冬、玉竹、太子參的神經(jīng)網(wǎng)絡(luò)模型。(4)建立了麥冬、玉竹、太子參三種藥材的相應(yīng)顯微組織特征參數(shù)與化學(xué)成分含量的聯(lián)系。(5)實現(xiàn)了麥冬藥材的性狀及組織特征的自動化提取。結(jié)論:本文基于顯微攝像技術(shù)以及計算機(jī)圖像處理技術(shù)的結(jié)合,較好地完成了麥冬、玉竹、太子參三種藥材的常見鑒定特征的定量分析,同時構(gòu)建了識別對應(yīng)中藥材的神經(jīng)網(wǎng)絡(luò)模型。該技術(shù)能更準(zhǔn)確、客觀地描述出麥冬、玉竹、太子參的傳統(tǒng)鑒定特征,這為將來識別中藥材的品種、產(chǎn)地等奠定基礎(chǔ)。該技術(shù)結(jié)合化學(xué)成分與所測得鑒定特征的相關(guān)性分析,能夠反映出中藥的成分與其常見鑒定特征的聯(lián)系,從而為從形態(tài)鑒定特征上評價和控制中藥的質(zhì)量提供了基礎(chǔ)的依據(jù)。
[Abstract]:Objective: to determine quantitatively the appearance and morphological characteristics of Ophiopogon japonicus, Phyllostachys heterophylla and Radix Pseudostellariae in different habitats, combined with computer image processing technique and camera technique. At the same time, the neural network recognition model of the selected medicinal materials from different habitats was constructed. Using image processing software to explore the corresponding algorithm, realize automation and batch operation as far as possible, and carry out histochemical localization and absorbance determination of the total saponins of medicinal materials from different habitats. The correlation between tissue characteristic parameters and chemical constituents was established. It provides a new way and method for the identification and quality standard control of traditional Chinese medicine. Methods: the samples were collected randomly and placed on white paper. The macroscopical images were taken by digital camera. Then, the medicinal materials taken were prepared by the polyethylene glycol embedding method, and the electronic eyepiece camera was used to move the field of vision without interval under the microscope, and the adjacent field of vision kept a certain repeating area. Continuously take a full picture of the microscopic images of medicinal materials. The microscopic image and the appearance image taken in front were processed by using the program of Matlab and Image Pro Plus image measurement software, and the macroscopic and microscopic characteristic parameters of different medicinal materials were measured. Collect the parameters needed for the experiment and make statistical analysis. The characteristics of the same medicinal materials from different regions or different parts were compared, and the characteristic vectors were constructed to identify this kind of medicinal materials. The pattern recognition toolbox of Matlab2014a was used to identify and analyze the medicinal materials. At the same time, correlation analysis was used to analyze the characteristics and chemical composition of the selected medicinal materials. The results showed that the shapes and colors of Ophiopogon japonicus, Phyllanthus heterophylla and Radix Pseudostellariae were realized. Quantitative description of size, surface texture features and tissue characteristics. (2) A method for mosaic of a large number of microscopic images was established. A neural network model for identification of Ophiopogon japonicus, Phyllostachys heterophylla and Radix Ophiopogonis japonicus was established. The relationship between the microstructural characteristic parameters and the content of chemical components of Radix Pseudostellariae heterophylla was used to realize the automatic extraction of the characters and tissue characteristics of Radix Ophiopogonis. Conclusion: based on the combination of microscopic camera technique and computer image processing technology, the quantitative analysis of common identification characteristics of Radix Ophiopogonis, Phyllostachys heterophylla and Radix Pseudostellariae was completed in this paper. At the same time, a neural network model for identifying the corresponding Chinese medicinal materials was constructed. This technique can more accurately and objectively describe the traditional identification characteristics of Ophiopogon japonicus, Phyllostachys heterophylla and Radix Pseudostellariae, which will lay a foundation for the identification of varieties and habitats of Chinese medicinal materials in the future. This technique can reflect the relationship between the components of traditional Chinese medicine and their common identification characteristics, and provide the basis for evaluating and controlling the quality of traditional Chinese medicine from the aspect of morphological identification.
【學(xué)位授予單位】：廣州中醫(yī)藥大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

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本文編號：1949678