Some test strips have high feasibility for the quick and approximate quantification of the biochemical substances in samples. Recently, test strips became more precise and accurate by involving the quantitative observation of coloration and regression modelling. Their accuracy and precision can be significantly improved by hue-shifting the colours of the original sample and those of the standards. The standard colour images included in the instructions of test strips for the detection of four urinary and two salivary biochemical substances were used. Images of glucose-loaded test strips for urinary glucose detection were also prepared. Using the red-green-blue (RGB) colour image, the author prepared 11 hue-shifted colour images by changing the hue of the original RGB colour image at intervals of 30°. From each of the 12 colour images, 10 greyscale images indicating values of the intensity of RGB, cyan, magenta, yellow, key black, L*, a* and b* were prepared. In regression modelling, the additional 110 greyscale images improved the values of the coefficient of determination and normalised mean absolute error in the quantification of protein, specific gravity, urobilinogen and glucose in urine, as well as of alcohol and nitric oxide in saliva. Further analyses showed that the hue-shifting technique yielded new greyscale images that were more significantly related to the values of the biochemical variables in question than any previous greyscale images. This improvement was realised by the most significant linear measures for the description of concentrations of biochemical substances, and synergetic effects between significant greyscale images.

中文翻译：

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使用诊断试纸准确和精确量化生化物质的色调转换

一些试纸对于样品中生化物质的快速近似定量具有很高的可行性。最近，通过涉及着色和回归建模的定量观察，试纸变得更加精确和准确。通过对原始样品和标准品的颜色进行色调转换，可以显着提高它们的准确度和精确度。使用检测四种尿液生化物质和两种唾液生化物质的试纸说明书中包含的标准彩色图像。还准备了用于检测尿糖的葡萄糖测试条的图像。使用红绿蓝(RGB)彩色图像，作者通过以30°的间隔改变原始RGB彩色图像的色调，制备了11幅色调偏移的彩色图像。从 12 个彩色图像中的每一个，制备L*、a*和b*。在回归建模中，额外的 110 个灰度图像改进了蛋白质、比重、尿胆素原和尿液中葡萄糖以及唾液中酒精和一氧化氮定量的测定系数和归一化平均绝对误差的值。进一步的分析表明，色调偏移技术产生了新的灰度图像，与之前的任何灰度图像相比，这些图像与所讨论的生化变量的值更显着相关。这种改进是通过描述生化物质浓度的最显着线性度量以及显着灰度图像之间的协同效应实现的。