Combing the color transmission image and the Beer–Lambert law shows a great application prospect in quantifying each material in multilayer specimen. Here, a novel, low-cost, and efficient optical algorithm is proposed to predict the thickness of each color material in a multilayer specimen from the color transmission image based on the Beer–Lambert Law. In this work, a normal scanner is employed to achieve the color transmission image of the monochrome transparent films. RGB values represent the transmitted intensity. A linear relationship between the optical depth and physical thickness is observed under different monochromatic lights. It is supposed that for a multilayer transparent film which consisted of different monochrome transparent films, the optical depth is related to the physical thickness of each monochrome transparent component. Therefore, an estimating equation is proposed to predict the thickness of each color material in the multilayer specimen. According to the result, the standard deviation of predicted thickness and practical thickness of each color film in the multilayer specimen is 0.93%. Fairly good agreement and high accuracy are obtained between the practical and predicted values, and the validity of this method is confirmed.

中文翻译：

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基于透射图像量化多层透明试样中各色料的厚度

将彩色透射图像与 Beer-Lambert 定律相结合，在量化多层样品中的每种材料方面显示出巨大的应用前景。在这里，提出了一种新颖、低成本、高效的光学算法，根据比尔-兰伯特定律，从彩色透射图像中预测多层样品中每种颜色材料的厚度。在这项工作中，使用普通扫描仪来实现单色透明胶片的彩色透射图像。RGB 值表示透射强度。在不同的单色光下观察到光学深度和物理厚度之间的线性关系。假设对于由不同单色透明薄膜组成的多层透明薄膜，光学深度与每个单色透明组件的物理厚度有关。因此，提出了一个估计方程来预测多层样品中每种颜色材料的厚度。结果表明，多层试件中各色膜的预测厚度与实际厚度的标准差为0.93%。实际值与预测值之间具有较好的一致性和较高的准确度，证实了该方法的有效性。