光谱学与光谱分析, 2018, 38 (8): 2488, 网络出版: 2018-08-26  

Stearns-Noechel模型的全光谱纱线配色算法

All Spectral Yarn Color Matching Algorithm Based on Stearns-Noechel Model
作者单位
1 天津工业大学纺织学院, 天津 300387
2 天津工业大学先进纺织复合材料重点实验室, 天津 300387
3 烟台南山学院, 山东 龙口 265706
摘要
目前计算机配色中, 拟合样与标准样的色差小时配方偏差较大, 打样结果不理想, 难以预测准确配方。 在光学模型Stearns-Noechel模型的基础上进行算法优化。 利用两个样品的分光反射率数据相等, 则两个样品必然等色的特性, 改进计算机配色算法程序中的判别条件, 即通过MATLB编程计算, 在区间[0 1]中, 每间隔0.001, 循环未知参数M值, 选择全光谱反射率数据偏差最小时的参数M值计算拟合配比, 代替色差最小时的参数M值计算拟合配比, 并分别计算拟合样与标准样的相对配方偏差进行对比。 结果表明, 选择全光谱反射率数据偏差最小时参数M值对应的拟合配方, 一次色的平均配方相对偏差为0.560, 二次色为0.346; 选择色差最小时参数M值对应的拟合配方, 一次色的平均配方相对偏差为0.723, 二次色为0.383; 两种方法对比, 可以看出无论是一次色还是二次色, 优化算法后拟合样品与标准样品的配方相对偏差都比选择色差最小时对应的的相对配方偏差小, 即优化后的拟合配方更加接近真实配方, 配色精确度得到明显提高, 有利于减少后期打样次数, 提高配色效率。
Abstract
At present, computer color matching is difficult to predict the exact formulation of the problem when color difference formula hours large deviations, so the algorithm is optimized based on the Stearns-Noechel model of the optical model. Using the spectral reflectance data of the two samples were equal and the two samples necessarily colored,and then the discriminant conditions in the computer color matching algorithm program were improved. We Calculated by MATLB, in the interval [0 1], every interval of 0.001, the cycle of unknown parameters M value, and selected the full spectrum of the reflectance data when the minimum deviation of the parameter M value to calculate the fit ratio, instead of the minimum color parameters M. The fitting ratio wascalculated and the relative formula deviation of the fitting sample was calculated. The results showed that the average deviation of the average color of the primary color was 0.560 and the secondary color was 0.346 when the deviation of the parameter M was the minimum of the total spectral reflectance data. The minimum deviation of the parameter M was the corresponding formula, the relative deviation of the primary color was 0.723, and the secondary color was 0.383. Compared with the two methods, it can be seen that the relative deviation of the formula after fitting the sample and the standard sample was smaller than the relative formula deviation when the chromatic aberration was minimum. That is, after the optimization of the formula was more close to the real formula, and color accuracy has been significantly improved, helping to reduce the number of late proofing as well as improving color efficiency.

马崇启, 程璐, 金晓, 买巍, 刘建勇, 朱宝基. Stearns-Noechel模型的全光谱纱线配色算法[J]. 光谱学与光谱分析, 2018, 38(8): 2488. MA Chong-qi, CHENG Lu, JIN Xiao, MAI Wei, LIU Jian-yong, ZHU Bao-ji. All Spectral Yarn Color Matching Algorithm Based on Stearns-Noechel Model[J]. Spectroscopy and Spectral Analysis, 2018, 38(8): 2488.

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