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RGB Color Calibration for Quantitative Image Analysis: The 3D Thin-Plate Spline Warping Approach

机译:用于定量图像分析的RGB颜色校准: 3D薄板样条变形方法

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摘要

In the last years the need to numerically define color by its coordinates in n-dimensional space has increased strongly. Colorimetric calibration is fundamental in food processing and other biological disciplines to quantitatively compare samples' color during workflow with many devices. Several software programmes are available to perform standardized colorimetric procedures, but they are often too imprecise for scientific purposes. In this study, we applied the Thin-Plate Spline interpolation algorithm to calibrate colours in sRGB space (the corresponding Matlab code is reported in the Appendix). This was compared with other two approaches. The first is based on a commercial calibration system (ProfileMaker) and the second on a Partial Least Square analysis. Moreover, to explore device variability and resolution two different cameras were adopted and for each sensor, three consecutive pictures were acquired under four different light conditions. According to our results, the Thin-Plate Spline approach reported a very high efficiency of calibration allowing the possibility to create a revolution in the in-field applicative context of colour quantification not only in food sciences, but also in other biological disciplines. These results are of great importance for scientific color evaluation when lighting conditions are not controlled. Moreover, it allows the use of low cost instruments while still returning scientifically sound quantitative data.
机译:近年来,通过n维空间中的坐标在数字上定义颜色的需求已大大增加。比色校准是食品加工和其他生物学科的基础,可以使用许多设备在工作流程中定量比较样品的颜色。有几种软件程序可用于执行标准化的比色程序,但出于科学目的,它们通常过于不精确。在这项研究中,我们应用了薄板样条插值算法来校准sRGB空间中的颜色(相应的Matlab代码在附录中报告)。将此与其他两种方法进行了比较。第一个基于商业校准系统(ProfileMaker),第二个基于偏最小二乘分析。此外,为了探索设备的可变性和分辨率,采用了两个不同的相机,并且对于每个传感器,在四个不同的光照条件下获取了三张连续的图片。根据我们的结果,Thin-Plate Spline方法报告了很高的校准效率,这不仅使食品科学领域,而且也使其他生物学科的现场应用中的颜色量化成为可能。当不控制照明条件时,这些结果对于科学的色彩评估非常重要。此外,它允许使用低成本仪器,同时仍返回科学可靠的定量数据。

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