计算机应用 ›› 2012, Vol. 32 ›› Issue (06): 1598-1600.DOI: 10.3724/SP.J.1087.2012.01598

• 图形图像技术 • 上一篇    下一篇

基于模糊规则的印刷图像专色分色研究

杨玲1,2,钟云飞2,王彬3   

  1. 1. 北京印刷学院 印刷与包装工程学院,北京 102600
    2. 湖南工业大学 包装与材料工程学院,湖南 株洲 412007
    3. 湖南工业大学 电气与信息工程学院,湖南 株洲 412008
  • 收稿日期:2011-12-01 修回日期:2012-01-16 发布日期:2012-06-04 出版日期:2012-06-01
  • 通讯作者: 钟云飞
  • 作者简介:杨玲(1989-),女,湖南益阳人,硕士研究生,主要研究方向:印刷防伪材料、流变学;〓钟云飞(1975-),男,白族,湖南慈利人, 副教授,主要研究方向:图像处理、模式识别;〓王彬(1985-),男,山东临沂人,硕士研究生,主要研究方向:智能检测。
  • 基金资助:
    2011年度湖南工业大学自然科学研究项目;湖南省科技厅资助项目;国家自然科学基金资助项目;2011年度湖南省大学生研究性学习和创新性实验计划项目

Spot color separation of printing images based on fuzzy rules

YANG Ling1,2,ZHONG Yun-fei1,WANG Bin3   

  1. 1. School of Packaging and Materials Engineering, Hunan University of Technology , Zhuzhou Hunan 412007 China
    2. School of Printing and Packaging Engineering, Beijing Institute of Graphic Communication, Beijing 102600 China
    3. School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou Hunan 412008 China
  • Received:2011-12-01 Revised:2012-01-16 Online:2012-06-04 Published:2012-06-01
  • Contact: ZHONG Yun-fei
  • Supported by:
    ;project supported by Hunan provincial science & technology department

摘要: 现有印刷图像专色分色技术已经不能满足印前处理效率和印刷质量要求,针对这一现状,提出了一种模糊C-均值聚类算法(FCM)。该算法基于像素分类,它首先对图像的灰度级进行模糊聚类,得到图像的聚类中心,然后根据每个像素点的灰度级,依照最大隶属度原则将各个像素点归于相应的类别中。实验证明,采用FCM 对印刷图像进行分割具有直观、易于实现的特点,实现了较好的分割效果。

关键词: 专色分色, 模糊聚类, 聚类中心, 隶属度, 彩色印刷

Abstract: The existing technology of color separation, especially the spot color separation, can no longer meet the requirements of prepress processing efficiency or printing quality.Aimed at this situation, the fuzzy C-means clustering algorithm(FCM) was put forward. The algorithm, based on the classification of pixels, carried fuzzy clustering on the grayscale of images in order to get image clustering center at first, and then put each pixel to the corresponding category according to the grayscale of each pixel and the maximum membership degree. Experimental result shows that image segmentation based on fuzzy rules is intuitive and easy to realize and has achieved a good segmentation effect.

Key words: spot color separation, fuzzy clustering, clustering center, membership grade, color printing