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J4 ›› 2010, Vol. 45 ›› Issue (7): 76-80.

• 论文 • 上一篇    下一篇

一种新的基于区域生长的彩色图像分割算法

刘战杰1,马儒宁1,邹国平1,钟宝江2,丁军娣3   

  1. 1. 南京航空航天大学理学院, 江苏 南京 211100;
    2. 苏州大学计算机科学与技术学院, 江苏 苏州 215006;
    3. 南京理工大学计算机科学与技术学院, 江苏 南京 210094
  • 收稿日期:2010-04-02 出版日期:2010-07-16 发布日期:2010-09-06
  • 作者简介:刘战杰(1983-),男,硕士研究生,主要研究方向为图像分割、目标检测与识别.Email: sattoboy@sina.com
  • 基金资助:

    国家自然科学基金资助项目(60705014);航空科学基金资助项目(2009ZH52069)

An algorithm for color image segmentation based on region growth

LIU Zhan-jie1, MA Ru-ning1, ZOU Guo-ping1, ZHONG Bao-jiang2, DING Jun-di 3   

  1. 1. College of Science,Nanjing University of Aeronautics and Astronautics, Nanjing 211100, Jiangsu, China;
     2.  School of Computer Science & Technology, Soochow University, Suzhou 215006, Jiangsu, China;
    3. School of Computer Science and Technology, Nanjing University of Science and Technology,
    Nanjing 210094, Jiangsu, China
  • Received:2010-04-02 Online:2010-07-16 Published:2010-09-06

摘要:

为克服一般区域生长算法对初始种子点选择以及生长顺序鲁棒性较差的问题,提出了一种鲁棒于生长顺序的彩色图像区域生长算法.首先计算所有像素点的局部颜色直方图以及领域相似性指标(neighbor similarity factor,NSF);其次通过NSF值建立种子的选取准则、种子的生长准则以及生长的终止准则,对图像进行初分割;最后对未分类点进行重新分类得到最终分割结果。通过与JSEG算法比较发现,该算法在运算时间以及分割准确性具有明显优势。

关键词: 彩色图像分割;区域生长;邻域相似性指标

Abstract:

A color image segmentation algorithm was proposed under the framework of seeded region growing (SRG).Compared to existing SRG methods, this method was robust to the selection of initial seedpixels and the order of region growing. Specifically, there were three main steps: 1) computing a neighborhood based similarity factor (NSF) based on the local color histogram of each pixel; 2) building the criteria of seed selection, region growth and region termination principled by NSF; 3) assigning labels to those un-segmented pixels for a final segmentation. Experimental results showed the superior performance of our methods in computational complexity and segmentation accuracy to the popular method of JSEG.

Key words:  image segmentation; region growing; neighbor similarity factor

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