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Application of Total Variation Model in Prediction of Xuan Paper Printing Quality
Received:August 09, 2018  
DOI:10.11981/j.issn.1000-6842.2020.01.59
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Fund Project:国家自然科学基金(31270629)。
Author NameAffiliation
张琪 南京林业大学轻工与食品学院,江苏南京,210037 
金典 南京林业大学轻工与食品学院,江苏南京,210037 
于艺铭 南京林业大学轻工与食品学院,江苏南京,210037 
陈茜 南京林业大学轻工与食品学院,江苏南京,210037 
王小菊 南京林业大学轻工与食品学院,江苏南京,210037 
王琪 南京林业大学轻工与食品学院,江苏南京,210037 
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Abstract:
      In order to establish a paper printing quality prediction model suitable for Xuan paper, 14 kinds of Xuan paper's surface parameters such as roughness, whiteness, opacity, basis weight, gloss, were tested. According to the characteristics of Xuan paper, the parameters of depth and density of paper grains were specially set and measured. Chroma of the printed matter was measured under the same printing condition, total variation model was used to construct a measuring method which eliminated the influence of paper grains, and the chromatic aberration values in accord with human visual characteristics were obtained. And a prediction model was established by utilizing generalized regression neural network combined with Xuan paper's surface parameters and chromatic aberration value without the influence of paper grains. The results showed that the model could accurately predict the paper printing quality by measuring the surface physical properties of Xuan paper only. This method provided guidance for paper selection before printing by measuring the specific surface parameters of Xuan paper.
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