基于图文信息的柔版印刷压力预测方法研究  

Flexographic printing pressure prediction method based on graphic feature information

作　　者：廖开阳 豆佳欣 武吉梅 LIAO Kaiyang;DOU Jiaxin;WU Jimei(School of Printing,Packaging Engineering and Digital Media Technology,Xi’an University of Technology,Xi’an 710048,China)

机构地区：[1]西安理工大学印刷包装与数字媒体学院,陕西西安710048

出　　处：《西安理工大学学报》2020年第4期562-568,共7页Journal of Xi'an University of Technology

基　　金：陕西省自然科学基金资助项目(2018JM5023)。

摘　　要：印刷压力是印刷质量的根本保证,为了减少目前印刷压力预测系统依赖性高和价格高的问题,提出了一种基于图文信息的柔版印刷压力预测方法。该方法通过对印刷原稿的分析,提取了原稿的图文面积、图文分布和最大梯度值三种图文特征信息,建立基于图文特征信息和最佳印刷压力预测模型。实验结果表明该方法能够实现最佳印刷压力的有效预测,减少了印刷压力预测系统依赖性高和价格度高的问题,对柔版印刷机的智能化发展有重要意义。Printing pressure is the fundamental guarantee of printing quality.In order to reduce the high dependence and high price of printing pressure prediction system,a flexographic printing pressure prediction method based on graphic information is proposed.By analyzing the printed originals,the using method extracts the three kinds of graphic feature information:the original graphic area,the graphic distribution and the maximum gradient value,thus establishing the image based on the graphic feature information and the optimal printing pressure prediction model.The experimental results show that the method can effectively predict the optimal printing pressure and reduce the dependence of printing pressure prediction system and high price,and it is of great significance to the intelligent development of flexographic printing machine.

关 键 词：印刷压力 印刷原稿 卷积神经网络 柔性版印刷 

分 类 号：TS803.6[轻工技术与工程]