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Quantification of carbohydrate based on scan image analysis for TLC technique compensating lack of spot overlaps

机译:基于TLC技术的扫描图像分析来定量碳水化合物补偿缺失斑点重叠的扫描图像分析

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In this paper, a quantification method of the carbohydrate is proposed for samples of spot tests using the thin-layer chromatography (TLC) based on the scanned image analysis compensating lack of overlap between each spot. The color density of image data is modeled by 2-dimensional Gaussian function. Parameters in the Gaussian function are estimated by calculating marginal distribution and using least squares (LS) method. Sample image of the spots on the TLC plate are quantified as calculating the volume of Gaussian function. A numerical example is then carried out for quantifying the glucose which is an important and commonly unit of the carbohydrate. The efficiency of our method is pointed out comparing with two non-compensated methods. In addition, in order to investigate the performance of proposed method, calibrated values are also compared with results using the high performance liquid chromatography (HPLC).
机译:在本文中,提出了一种基于扫描图像分析补偿每个斑点之间的扫描图像分析的薄层色谱(TLC)来试验测试的定位试验样品。图像数据的颜色密度由二维高斯函数建模。通过计算边缘分布和使用最小二乘(LS)方法来估计高斯函数中的参数。 TLC板上的斑点的样本图像被量化为计算高斯功能的体积。然后对数值例进行用于量化葡萄糖,这是碳水化合物的重要且通常单位的葡萄糖。我们的方法的效率与两种非补偿方法相比,指出了比较。另外,为了研究所提出的方法的性能,还将校准值与使用高效液相色谱(HPLC)进行比较。

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