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A Regression Model of Color Value and Substance Concentration of Colored Solution Based on Lambert Beer’s Law

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Cyber Security Intelligence and Analytics (CSIA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1146))

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Abstract

The paper is systematically discussed the regression model analysis based on Lambert Beer’s law on the color readings of different solution materials and the concentration of substances is discussed. The data is standardized and the evaluation of the given data is completed. We derive the relevant scale factor equation according to Lambert Beer’s law and establish a regression model of the color reading mean and material concentration of different solutions. In this paper, the concentration of the solution is first determined by measuring and comparing the color depth of the colored solution, and the value of R (red) G (green) B (blue) in the photograph is extracted by photographing using the different colors of the colored solution on the colorimetric test paper. By preprocessing and normalizing the data of these five different data indicators, a regression model between the RGB values of the colors and the concentration values of the colored solutions is established, and the correlation between them is determined to determine the reliability of the data. Sexuality, so that this model can be popularized and applied, and the concentration of the solution can be read efficiently and quickly by using the RGB value, chromaticity, and saturation value of the colored solution.

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Acknowledgements

This work was supported by the Beijing Municipal Natural Science Foundation (No. 4172006).

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Correspondence to Lijing Liu .

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Song, X., Liu, L. (2020). A Regression Model of Color Value and Substance Concentration of Colored Solution Based on Lambert Beer’s Law. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1146. Springer, Cham. https://doi.org/10.1007/978-3-030-43306-2_114

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