文章摘要
孙小鹏,孔玲君,刘真.基于胞元式 RBF 神经网络的高保真分色模型研究[J].包装工程,2013,34(1):110-114.
SUN Xiao-peng,KONG Ling-jun,LIU Zhen.Research of Hi-Fi Color Separation Model Based on Cellular RBF Neural Network[J].Packaging Engineering,2013,34(1):110-114.
基于胞元式 RBF 神经网络的高保真分色模型研究
Research of Hi-Fi Color Separation Model Based on Cellular RBF Neural Network
投稿时间:2012-08-20  修订日期:2013-01-10
DOI:
中文关键词: 七色分色模型  高保真印刷  分区  胞元  RBF 神经网络
英文关键词: seven-color separation model  Hi-Fi color printing  partition  cell  RBF neural network
基金项目:上海市科委项目(09220502700);国家新闻出版总署数字印刷工程研究中心开放基金项目
作者单位
孙小鹏 上海理工大学, 上海 200093 
孔玲君 1. 上海理工大学, 上海 200093
2. 上海出版印刷高等专科学校, 上海 200093 
刘真 上海理工大学, 上海 200093 
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中文摘要:
      采用胞元式 RBF 神经网络模型对七色印刷输出系统构建了分色模型。 首先,借鉴颜色空间分区理论将7 个主色在整个颜色空间中划分为了 6 个颜色区域,在每个分区中选取了 CIE L*a*b*明度值 L 上等间隔均匀采样的网点面积率,用于设计建模所需的训练样本,然后对每个分区划分胞元,并且为每个小胞元建立了基于RBF 神经网络的分色模型。 对于任意给定的要复制的目标色,利用提出的胞元搜索算法确定其所在的胞元位置后,使用相应的神经网络模型进行分色预测。 实验结果表明,该分色算法能够达到较高的分色精度,可以满足高质量彩色复制的要求。
英文摘要:
      Color separation models for seven-color printing system were established using cellular RBF neural network. Firstly, according to color space partition theory, the color space of the printing system was divided into 6 partitions by 7 primary colors. Dot areas, which were sampled from L of CIE L*a*b* with equal space, were then selected as training samples of RBF neural network model in each partition. Each partition was subdivided into several cells and the color separation algorithm based on RBF neural network model for each cell was established. Any target color would be separated into the CMYKRGB dot areas according to the color separation models of the numbered cell which were determined by the cell search algorithm proposed. The experiment result showed that the color separation algorithm can achieve high accuracy of color separation for seven-color print production.
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