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Color Prediction for Pre-Colored Cotton Fiber Blends Based on Improved Kubelka-Munk Double-Constant Theory

Authors :
Lei Wang
Ruru Pan
Weidong Gao
Ge Zhang
Zhou Jian
Source :
Fibers and Polymers. 22:412-420
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

The accuracy of color prediction results for pre-colored fiber blends is critical in the textile industry. In this paper, we attempt to investigate a feasible method for predicting the color of pre-colored fibers blends. Five pre-colored cotton fibers were divided into two groups, one for achromatic primaries (white and black) and one for chromatic primaries (red, blue, and yellow). Their respective absorption coefficient (K) and scattering coefficient (S) were calculated by the least squares method from the prepared fiber blends samples. The color information of the 34 test blending samples including two-primary and three-primary was predicted by the improved Kubelka-Munk (K-M) double-constant theory. Comparing with the measurement results, the minimum and maximum DE00 color differences were 0.215 and 1.890. The variance of color difference for two-primary samples was 0.128 and for three-primary samples was 0.154, both were smaller than that obtained by the K-M theory relative value method, the Stearns-Noechel (S-N) model, revised S-N models, and the Friele model. The results show that the improved K-M double-constant theory can be used to better predict the color blending effect of pre-colored fibers.

Details

ISSN :
18750052 and 12299197
Volume :
22
Database :
OpenAIRE
Journal :
Fibers and Polymers
Accession number :
edsair.doi...........504532ddf8a75edea7904989170607e5
Full Text :
https://doi.org/10.1007/s12221-021-9371-z