The Hyperspectral Imaging System can obtain the spectral response value of each pixel in a fabric sample image while being applied to fabric color measurement. Compared with the common grating Hyperspectral Imaging System, the Hyperspectral Imaging System based on Liquid Crystal Tunable Filter (LCTF) has the advantages of small size, high spatial resolution, and easy integration, which has potential application prospects in textile industry. In this article, the performance of the LCTF Hyperspectral Imaging System for fabric color measurement was evaluated, and an improved model for calibrating the consistency between it and Datacolor 650 was proposed. First, the 210 Pantone cotton color cards were used as samples to study the color repeatability and reproducibility of the LCTF Hyperspectral Imaging System. For evaluation its color measurement ability, the measured reflectance values were converted to the CIELAB color space and compared with those of Datacolor 650. Then, a Radial Basis Function neural network model was proposed to calibrate the color consistency between LCTF Hyperspectral Imaging System and Datacolor 650 which can fully use the reflectance information of the whole band instead of only adjacent wavelengths. Experimental results show that the LCTF Hyperspectral Imaging System can accurately measure the fabric color with good repeatability and reproducibility, and the consistency between the two instruments was significantly improved based on the Radial Basis Function neural network model compared with the R model.

中文翻译：

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基于液晶可调滤光片织物颜色测量的高光谱成像系统评价与一致性标定

高光谱成像系统在应用于织物颜色测量的同时，可以获得织物样本图像中每个像素点的光谱响应值。与普通光栅高光谱成像系统相比，基于液晶可调滤光片（LCTF）的高光谱成像系统具有体积小、空间分辨率高、易于集成等优点，在纺织行业具有潜在的应用前景。在本文中，评估了 LCTF 高光谱成像系统在织物颜色测量中的性能，并提出了一种改进的模型来校准它与 Datacolor 650 之间的一致性。首先，以 210 张 Pantone 棉色卡为样本，研究 LCTF 高光谱成像系统的颜色重复性和再现性。为了评估其颜色测量能力，将测量的反射率值转换为 CIELAB 颜色空间，并与 Datacolor 650 进行比较。然后，提出径向基函数神经网络模型来校准 LCTF 高光谱成像系统和 Datacolor 650 之间的颜色一致性它可以充分利用整个波段的反射率信息，而不仅仅是相邻波长。实验结果表明，LCTF高光谱成像系统能够准确测量织物颜色，具有良好的重复性和再现性，基于径向基函数神经网络模型与R模型相比，两种仪器之间的一致性显着提高。然后，提出了径向基函数神经网络模型来校准LCTF高光谱成像系统和Datacolor 650之间的颜色一致性，该模型可以充分利用整个波段的反射率信息，而不仅仅是相邻波长。实验结果表明，LCTF高光谱成像系统能够准确测量织物颜色，具有良好的重复性和再现性，基于径向基函数神经网络模型与R模型相比，两种仪器之间的一致性显着提高。然后，提出了径向基函数神经网络模型来校准LCTF高光谱成像系统和Datacolor 650之间的颜色一致性，该模型可以充分利用整个波段的反射率信息，而不仅仅是相邻波长。实验结果表明，LCTF高光谱成像系统能够准确测量织物颜色，具有良好的重复性和再现性，基于径向基函数神经网络模型与R模型相比，两种仪器之间的一致性显着提高。