In order to improve the accuracy and applicability of computer color matching algorithm for color spunyarns, a full-spectrum color matching algorithm was proposed based on the classical Stearns Noechel optical theoretical model, aiming at the problems that it is difficult to minimize error in calculated color difference value and that in matching relative deviation. The sensitivity coefficient of human visual characteristics to reflected light at different wavelengths was determined by exploring human visual characteristics, and it was introduced into the color matching algorithm for weighted calculation to predict the monochrome fiber mixing ratio. The color matching effect was evaluated by predicting the color difference value, the relative deviation value of the ratio and the Euclidean distance. Results show that the color matching algorith with Poisson distribution introduced to the human eye sensitivity coefficient is optimal, with the average prediction color difference value being 0. 29 and all within 1, the ratio of the average relative deviation value being minimal 0. 612, Euclidean distance average being 0. 087 which is relatively small. When using the improved color matching algorithm, the prediction of the color difference value can be achieved through one calculation, leading to a small color difference with higher accuracy. With the improved algorithm, computer assisted color matching for color spunyarns can be primarily achieved.
关键词
色纺纱/全光谱配色/视觉特性/色差/配比相对偏差/计算机配色算法
Key words
color spun yarn/full spectrum color matching/visual characteristic/color difference/relative deviation in color matching/computer color matching algorithm
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