樊丽娜.基于GRNN神经网络的凹印专色配色模型研究[J].包装工程,2018,39(7):204-208.
FAN Li-na.Gravure Spot-color Matching Model Based on GRNN Neural Network[J].Packaging Engineering,2018,39(7):204-208. |
| 基于GRNN神经网络的凹印专色配色模型研究 |
| Gravure Spot-color Matching Model Based on GRNN Neural Network |
| 投稿时间：2017-09-14 修订日期：2018-04-10 |
| DOI：10.19554/j.cnki.1001-3563.2018.07.037 |
| 中文关键词: 凹印 专色 GRNN 配色模型 |
| 英文关键词: gravure spot-color general regression neural network (GRNN) color matching model |
| 基金项目:浙江省教育厅科研项目（Y201636873）；浙江省社科联研究课题项目（2015N075） |
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| 中文摘要: |
| 目的 针对目前专色配色的现状，建立基于GRNN神经网络的凹印专色配色模型，以实现计算机配色。方法 参照孟塞尔色相环将颜色空间分区，调配专色墨色样获得训练样本，并使其均匀分布在孟塞尔色谱中。分析广义神经网络的优势和凹印专色配色的特点，尝试基于GRNN神经网络构建凹印专色配色模型。采用Matlab进行仿真训练，并借助MSE函数确定平滑因子SPREAD的值，最后用检验样本的目标色和配出色的色差来检验配色模型的精度。结果 通过网络仿真，确定当SPREAD为6.4时，测试样本的MSE值最小。由此确定配色模型，配出的40组色样和目标色的平均色差值为2.45，且97.5%的样本色差值小于6。结论 基于GRNN神经网络的凹印专色配色模型精度较高，可用于计算机配色。 |
| 英文摘要: |
| The work aims to establish a gravure spot-color matching model based on GRNN neural network in order to realize computer color matching, in view of the current status of spot-color matching. Color space was divided according to Munsell color cycle. Training samples were obtained by preparing spot-color samples which were uniformly distributed in the Munsell color spectrum. By analyzing the advantages of general regression neural network and the characteristics of gravure spot-color matching, the gravure spot-color matching model was constructed upon attempt based on GRNN neural network. Matalb was used for simulation training, and then the value of smoothing factor SPREAD was determined by means of MSE function. Finally, the accuracy of the color matching model was tested by the color difference between target color and matching color of tested samples. Through network simulation, the MSE value of tested samples was determined to be the minimum when SPREAD was 6.4. A color matching model was thus determined. The average color difference between target color and matched color of 40 groups of tested samples was 2.45, and the color difference of 97.5% samples was less than 6. The gravure spot-color matching model based on GRNN neural network has higher precision and can be used in computer color matching. |
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