Enhanced beetle antennae search algorithm for spot color prediction

Q3 Engineering

西北工业大学学报 Pub Date : 2022-12-01 DOI:10.1051/jnwpu/20224061422

Zehai Gao, Yang Liu, Jie Chen, Molin Chu, Yan Zhang, Changsen Li

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引用次数: 0

Abstract

专色的准确预测是包装印刷领域的重要技术之一。为了得到更加准确的专色配方, 提高专色配色精度, 提出了一种结合最小二乘法和增强天牛须搜索算法的专色配方预测方法, 并利用吸光度来解决专色配方的预测问题。研究了高透光特性PET薄膜的光谱模型, 并构建了吸收光谱机理模型; 提出了增强天牛须搜索算法, 在传统天牛须搜索算法的基础上, 引入突变概率项和方向修正项, 提升算法的搜索能力和收敛速度; 利用最小二乘法优化配色色域空间, 降低基色搜索维度, 提高寻优效率。应用所提出的增强天牛须搜索算法求解各基色比例, 预测专色配方, 并与传统天牛须算法、粒子群算法和蚁群算法进行比较, 验证所提方法在专色预测方面的有效性和优越性。研究结果表明, 所提方法与现有的3种方法相比, 具有更高的精度, 原有专色和预测专色之间色差均小于3, 且90%的色差小于1, 40%的色差小于0.1, 所提方法对于提高专色油墨的配色精度具有显著效果, 可准确地预测专色配方。

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用于斑点颜色预测的增强型甲虫天线搜索算法

Accurate prediction of spot colors is one of the important technologies in the field of packaging and printing. In order to obtain more accurate spot color formulas and improve the accuracy of spot color matching, a spot color formula prediction method combining least squares method and enhanced longicorn whisker search algorithm was proposed, and absorbance was used to solve the problem of spot color formula prediction. Studied the spectral model of high transmittance PET film and constructed an absorption spectral mechanism model; We proposed an enhanced longicorn whisker search algorithm, which introduces mutation probability terms and direction correction terms on the basis of traditional longicorn whisker search algorithms to improve the search ability and convergence speed of the algorithm; Optimize the color gamut space using the least squares method, reduce the search dimension of the primary color, and improve the optimization efficiency. The proposed enhanced longicorn whisker search algorithm is applied to solve the proportion of each primary color, predict the spot color formula, and compare it with traditional longicorn whisker algorithm, particle swarm algorithm, and ant colony algorithm to verify the effectiveness and superiority of the proposed method in spot color prediction. The research results show that the proposed method has higher accuracy compared to the existing three methods. The color difference between the original spot color and the predicted spot color is less than 3, and 90% of the color difference is less than 1, while 40% of the color difference is less than 0.1. The proposed method has a significant effect on improving the color matching accuracy of spot color inks and can accurately predict spot color formulas.

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