Model and Method of Ink Components Proportion Prediction

LI Chan; WAN Xiao-xia; LYU Wei

doi:10.3788/fgxb20194005.0673

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Model and Method of Ink Components Proportion Prediction

Luminescence Applications and Interdisciplinary Fields | 更新时间：2020-08-12

- Model and Method of Ink Components Proportion Prediction
- Chinese Journal of Luminescence Vol. 40, Issue 5, Pages: 673-679(2019)
- 作者机构：
  
  1. 武汉大学印刷与包装系, 湖北武汉 430079
  2. 深圳劲嘉集团股份有限公司, 广东深圳 518105
- 作者简介：
- 基金信息：
  
  Supported by National Natural Science Foundation of China(61275172,61575147)
- DOI：10.3788/fgxb20194005.0673
  CLC： O433.4
- Received：27 June 2018，
  
  Revised：30 October 2018，
  
  Published Online：15 October 2018，
  
  Published：05 May 2019
- 稿件说明：
移动端阅览
李婵, 万晓霞, 吕伟. 油墨组分比例预测模型与方法[J]. 发光学报, 2019,40(5): 673-679

LI Chan, WAN Xiao-xia, LYU Wei. Model and Method of Ink Components Proportion Prediction[J]. Chinese Journal of Luminescence, 2019,40(5): 673-679
李婵, 万晓霞, 吕伟. 油墨组分比例预测模型与方法[J]. 发光学报, 2019,40(5): 673-679 DOI： 10.3788/fgxb20194005.0673.

LI Chan, WAN Xiao-xia, LYU Wei. Model and Method of Ink Components Proportion Prediction[J]. Chinese Journal of Luminescence, 2019,40(5): 673-679 DOI： 10.3788/fgxb20194005.0673.

摘要

因光学特性（吸收系数与散射吸收）与组分比例不呈严格的线性关系，基于K-M理论的配色模型无法保证比例预测精度，针对上述问题，建立了油墨组分比例预测模型与方法。首先利用与组分比例具有强线性相关性的特征波长处的光谱反射率倒数值替换K-M配色理论中的吸收系数与散射系数，引入非线性项，构建油墨混合呈色模型；然后在此基础上建立油墨组分比例预测模型。以两组二元基色油墨混合样本为例，对提出的油墨组分比例预测模型及方法进行验证。实验结果表明，文中方法可预测获得与真实结果较为接近的组分比例，两组实验样本的预测平均偏差分别为1.57%和3.6%，可为目标样油墨组分比例预测提供一种新的方法。

Abstract

Because the optical properties(absorption coefficient and scattering coefficient) do not have a strict linear relationship with the components proportion

the K-M based color matching model cannot guarantee the prediction precision of components proportion. In view of the problem mentioned above

this paper proposes an ink components proportion prediction model. First

an ink mixing model is established by replacing the absorption coefficient and scattering coefficient in the K-M theory with the reciprocal of spectral reflectance which has a strong linear correlation with the component proportion in certain characteristic wavelengths and introducing a additional nonlinear term. On this basis an ink components proportion prediction model is established. Taking two groups of samples mixed with binary primary inks as an example

the proposed model and method were verified. The experimental results showed that this method could predict components proportion that were close to the real results. The prediction average deviations of the two groups were 1.57% and 3.6% respectively. The proposed model and method can provide a new possibility for the ink components proportion prediction of target sample.

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references

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