A Novel Correction Method of Kubelka–Munk Model for Color Prediction of Pre-colored Fiber Blends

Abstract

In order to apply the single-constant Kubelka–Munk (KM) model to color prediction of fiber blends, a novel correction method is proposed in the paper. The single-constant KM model is based on the assumption that the ratio of absorption coefficients to scattering coefficients (K/S) of a mixture is linear to mass proportion of its components. However, when it comes to the media of pre-colored fiber blends, the linear assumption always fails, resulting in inaccurate color prediction with large color difference. To solve this problem, a novel correction method was proposed, which improved the linearity of K/S in the way of decreasing the linear deviation. Pre-colored cotton fibers were used to prepare samples to examine the proposed correction method. The average color difference values ΔE_cmc (2:1) and ΔE₀₀ of the single-constant KM model with proposed correction method are 1.37 and 1.17 respectively, which are remarkably better than those of the Kubelka–Munk model without correction (~ 8.41 and 6.35) and the Kubelka–Munk model with Saunderson correction (~ 8.63 and 6.55). The results indicate that, for the media of pre-colored fiber blends, the proposed correction method greatly improves the color prediction accuracy.