A Stearns‐Noechel color prediction model reconstructed from gridded color solid of nine primary colors and its application

Abstract

A full gamut color solid model consisting of three lightness planes, 18 color mixing units and 360 grid points is constructed from nine primary colored fibers: red (R), yellow (Y), green (G), cyan (C), blue (B), magenta (M), dark gray (O¹), medium gray (O²) and light gray (O³). Subsequently, the 213 colored yarns and fabrics containing different lightness, hue and saturation were prepared according to the mixing ratio parameters in the color solid. The Stearns‐Noechel color prediction algorithm, which predicts reflectance using colored fiber mixing ratios, was improved and applied according to the requirements of color prediction; and the Stearns‐Noechel proportion prediction algorithm, which predicts colored fiber mixing ratios by reflectance, was refined and employed in accordance with the demands of proportion prediction. Then, the 12 additional colored fabrics were fabricated and their corresponding measurement data were used on the algorithm for validating its forecasting capabilities. The final experimental results reveal that the maximum color difference for color prediction is 5.5, the minimum is 1.7, and the average is 3.7; the maximum color difference for proportion prediction is 3.3, the minimum is 0.3, and the average is 1.6. Therefore, this approach is promising to improve the color reproduction issues encountered in the processing of three‐channel CNC spinning.

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