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作 者:Manfei Xu Shengyun Dai Zhisheng Wu Xinyuan Shi Yanjiang Qiao
机构地区:[1]Beijing University of Chinese Medicine,Beijing 100102,China [2]Department of Pharmacy,The First Affiliated Hospital of Zhengzhou University,Zhengzhou,Henan 450052,China [3]Beijing Key Laboratory for Basic and Development Research on Chinese Medicine,Beijing,China [4]Key Laboratory of TCM-information Engineer of State Administration of TCM,Beijing,China
出 处:《Journal of Traditional Chinese Medical Sciences》2016年第4期234-241,共8页中医科学杂志(英文)
基 金:the Special Fund of Beijing University of Chinese Medicine(Grant 2015-JYBXS111,to MX).
摘 要:Objective:Rapid discrimination of three classes of safflowers,dyed safflower,adulterated safflower,and pure safflower using computer vision and image processing algorithms.Methods:A low cost computer vision system(CVS)was designed to measure the color of safflowers in the RGB(red,green,blue),L^*a^*b^*,and HSV(hue,saturation,vale)color spaces.The color moments in these three color spaces were extracted from the acquired images as color features of safflower.In addition,five kinds of pigments that are commonly used to dye safflowers were identified by high-performance liquid chromatography as a reference.Pattern recognition methods were investigated for rapid discrimination,including an unsupervised principal component analysis(PCA)algorithm and a supervised partial least squares discriminant analysis(PLS-DA)algorithm.Results:The mean error(e)between color values measured with the colorimeter and calculated with the CVS was 2.4%,with a high correlation coefficient(r)of 0.9905.This result indicated that the established CVS was reliable for color estimation of safflowers.The PLS-DA model,which had a total accuracy of 91.89%,outperformed the PCA model in classifying pure,adulterated,and dyed safflowers.Conclusion:The color objectification is a promising tool for rapid identification of dyed and adulterated safflowers.
关 键 词:SAFFLOWER COLORATION ADULTERATION Computer vision PCA PLS-DA
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术] R282.5[自动化与计算机技术—计算机科学与技术]
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