Agricultural Engineering Research Unit of the Agricultural Research Council (CRA-ING), Monterotondo scalo (Rome) 00015, Italy.
Sensors (Basel). 2012;12(6):7063-79. doi: 10.3390/s120607063. Epub 2012 May 29.
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.
在过去的几年中，人们强烈需要通过 n 维空间中的坐标来对颜色进行数值定义。比色校准在食品加工和其他生物学领域中非常重要，可以在工作流程中使用许多设备对样品的颜色进行定量比较。有几种软件程序可用于执行标准化的比色程序，但对于科学目的而言，它们通常不够精确。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）。这与其他两种方法进行了比较。第一种方法基于商业校准系统（ProfileMaker），第二种方法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，我们采用了两种不同的相机，并在四种不同的光照条件下对每个传感器采集了三张连续的照片。根据我们的结果，薄板样条方法的校准效率非常高，这使得在现场应用中进行颜色量化的方法发生变革成为可能，不仅在食品科学领域，而且在其他生物学领域也是如此。这些结果对于在不受控制的照明条件下进行科学的颜色评估非常重要。此外，它允许使用低成本的仪器，同时仍然返回科学合理的定量数据。
