A Corrected Kubelka-Munk Model for Color Prediction of Pre-colored Fiber Blends
Chun-ao Wei and Xiaoxia Wan, Wuhan University
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 single-constant 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.