计算机工程 ›› 2012, Vol. 38 ›› Issue (20): 184-187.doi: 10.3969/j.issn.1000-3428.2012.20.047

• 图形图像处理 • 上一篇    下一篇

基于云模型的多粒度彩色图像分割

马鸿耀 1a,王国胤 1a,张清华 1a,1b,徐 宁 2   

  1. (1. 重庆邮电大学 a. 计算机科学与技术研究所;b. 数理学院,重庆 400065;2. 西南交通大学信息科学与技术学院,成都 610031)
  • 收稿日期:2011-12-02 修回日期:2012-02-22 出版日期:2012-10-20 发布日期:2012-10-17
  • 作者简介:马鸿耀(1985-),男,硕士研究生,主研方向:图像处理,粒计算;王国胤,教授、博士生导师;张清华,副教授、博士;徐 宁,硕士研究生
  • 基金项目:

    国家自然科学基金资助项目(61073146);重庆市杰出青年科学基金资助项目(2008BA2041);重庆市教委科学技术研究基金资助项目(KJ110512)

Multi-granularity Color Image Segmentation Based on Cloud Model

MA Hong-yao 1a, WANG Guo-yin 1a, ZHANG Qing-hua 1a,1b, XU Ning 2   

  1. (1a. Institute of Computer Science and Technology; 1b. College of Mathematics and Physics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; 2. School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China)
  • Received:2011-12-02 Revised:2012-02-22 Online:2012-10-20 Published:2012-10-17

摘要: 图像信息中存在的不确定性问题会影响图像的分割效果。为此,提出一种基于粒计算和云模型的彩色图像分割算法。研究多粒度认知模型,在HSV颜色空间中利用云模型构建彩色图像的信息粒,进行多粒度、多层次的云粒合成,实现彩色图像分割。实验结果表明,与PCNN算法和K均值算法相比,该算法的分割效果较好。

关键词: 粒计算, 云模型, 彩色图像分割, 云变换, 多粒度, HSV空间

Abstract: Image information contains a lot of uncertainty which may cause the unsatisfactory image segmentation effect. In order to solve this problem, this paper proposes a algorithm of color image segmentation based on granular computing and cloud model. It granulates color images in HSV color space, and cloud-granule concept is generated in multi-granularity and multi-level, finally the color image is segmented. Experimental results show that the proposed algorithm has better performance compares with PCNN and K-means algorithm.

Key words: granular computing, cloud model, color image segmentation, cloud transformation, multi-granularity, HSV space

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