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A Corrected Kubelka-Munk Model for Color Prediction of Pre-colored Fiber Blends

机译:一种校正的Kubelka-Munk模型,用于预测前彩色纤维混合物

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The goal of this work is to propose a corrected single-constant Kubelka-Munk model for color prediction of pre-colored fiber blends. The K/S for the medium of pre-colored fiber blends does not hold good linearity with the proportion c, causing inaccurate color prediction of the single-constant model. Aiming at achieving good linearity of K/S, a new correction model for the measured reflectance has been established based on the inverse function of Sanderson correction. Cotton fibers blending samples were prepared to assess the color prediction accuracy. The average color difference of the corrected singleconstant Kubelka-Munk model was 0.82 CIEDE2000 unit, which was significantly better than that of the original model (~6.35). The results indicate the proposed model is much more suitable for color prediction of pre-colored fiber blends.
机译:这项工作的目标是提出一种校正的单常数Kubelka-Munk模型,用于预彩色纤维混合物的颜色预测。用于预色纤维混合物的培养基的K / S不会与比例C保持良好的线性度,导致单常数模型的不准确的颜色预测。旨在实现K / S的良好线性,基于桑德隆校正的逆功能建立了一种测量反射率的新校正模型。制备棉纤维混合样品以评估颜色预测精度。校正的SingleConstant Kubelka-Munk模型的平均色差为0.82 Ciede2000单位,其明显优于原始模型(〜6.35)。结果表明所提出的模型更适合于预色纤维混合物的颜色预测。

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