• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2015, Vol. 37 ›› Issue (01): 125-132.

• 论文 • 上一篇    下一篇

混合量子粒子群图像分割算法IS-MQPS

高颖慧1,曲智国1,卢凯2   

  1. (1.国防科学技术大学ATR国家重点实验室,湖南 长沙 410073;2.国防科学技术大学计算机学院,湖南 长沙 410073)
  • 收稿日期:2013-04-01 修回日期:2014-11-07 出版日期:2015-01-25 发布日期:2015-01-25
  • 基金资助:

    国家自然科学基金资助项目(61103082)

A novel image segmentation algorithm
based on mixed quantum particle swarm 

GAO Yinghui1,QU Zhiguo1,LU Kai2   

  1. (1.National Key Laboratory of Automatic Target Recognition,National University of Defense Technology,Changsha 410073;
    2.College of Computer,National University of Defense Technology,Changsha 410073,China)
  • Received:2013-04-01 Revised:2014-11-07 Online:2015-01-25 Published:2015-01-25

摘要:

基于群智能的图像分割技术因其与人类视觉机理相符合,受到人们重视。但是,现有群体模型存在的对参数取值敏感和易收敛于局部极值等问题,制约了群智能技术在复杂图像分割中的应用。首先定义了基于群智能图像分割的抽象模型,然后将通用量子粒子模型GQPM引进图像分割,提出了混合量子粒子群图像分割算法ISMQPS。ISMQPS算法以量子粒子携带灰度和坐标信息,以纠缠量子态定义群体行为规则,以混合量子粒子群的自组织聚类实现图像分割。实验表明,ISMQPS算法具有对噪声不敏感、分割区域意义明确等优点,可应用于复杂图像分割。

关键词: 图像分割, 群智能, 通用量子粒子模型, 混合量子粒子群

Abstract:

Image segmentation technology based on swarm intelligence has been paid more and more attentions due to its consistency with human visual mechanism. However, many existing swarm models are sensitive to parameter values and easy to converge to the local minimum, which restricts the application of swarm intelligence in complex image segmentation. In the paper, we define the abstract model of image segmentation based on swarm intelligence firstly, and then propose a novel image segmentation algorithm based on mixed quantum particle swarm (ISMQPS) by introducing the eneralized quantum particle model (GQPM) into image segmentation. ISMQPS contains three key parts: defining the quantum particle by pixel's grey value and position value, defining the swarm action rule by entangled quantum state, and realizing image segmentation by selforganization clustering of mixed quantum particle swarm. Experiments show that ISMQPS is insensitive to noise, has good segmentation effect, and can be used in complex image segmentation.

Key words:  image segmentation;swarm intelligence;generalized quantum particle model;mixed quantum particle swarm