A Stearns–Noechel colour prediction model reconstructed from gridded colour solid of nine primary colours and its application

Abstract

A full gamut colour solid model consisting of three lightness planes, 18 colour mixing units and 360 grid points is constructed from nine primary coloured fibres: red (R), yellow (Y), green (G), cyan (C), blue (B), magenta (M), dark grey (O¹), medium grey (O²) and light grey (O³). Subsequently, the 213 coloured yarns and fabrics containing different lightness, hue and saturation were prepared according to the mixing ratio parameters in the colour solid. The Stearns–Noechel colour prediction algorithm, which predicts reflectance using coloured fibre mixing ratios, was improved and applied according to the requirements of colour prediction; and the Stearns–Noechel proportion prediction algorithm, which predicts coloured fibre mixing ratios by reflectance, was refined and employed in accordance with the demands of proportion prediction. Then, the 12 additional coloured 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 colour difference for colour prediction is 5.5, the minimum is 1.7, and the average is 3.7; the maximum colour 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 colour reproduction issues encountered in the processing of three-channel computer numerical control (CNC) spinning.