J4 ›› 2011, Vol. 38 ›› Issue (6): 152-158+178.doi: 10.3969/j.issn.1001-2400.2011.06.025

• 研究论文 • 上一篇    下一篇



  1. (1. 陕西师范大学 计算机科学学院,陕西 西安  710062;
    2. 海南大学 应用科技学院,海南 儋州  571737)
  • 收稿日期:2010-10-08 出版日期:2011-12-20 发布日期:2011-11-29
  • 通讯作者: 马苗
  • 作者简介:马苗(1977-),女,副教授,博士,E-mail: mmthp@snnu.edu.cn
  • 基金资助:


SAR image thresholding segmentation based on the bacteria foraging algorithm

MA Miao1;LIANG Jianhui1,2;GUO Min1

  1. (1. College of Computer Sci., Shaanxi Normal Univ., Xi'an  710062, China;
    2. College of Applied Sci. adn Tech. of Hainan Univ., Danzhou  571737, China)
  • Received:2010-10-08 Online:2011-12-20 Published:2011-11-29
  • Contact: MA Miao



关键词: 图像分割, 细菌觅食算法, 全局优化, SAR图像


In order to increase the speed and the accuracy of Synthetic Aperture Radar(SAR) image segmentation, a new thresholding segmentation method is proposed, which integrates the Bacterial Foraging Algorithm (BFA) and two-dimensional grey entropy. After the basic BFA is analyzed deeply, the method improves the search speed of the best threshold via shrinking the foraging space of the bacterial swarm. And then, an improved two-dimensional grey entropy model is regarded as the fitness function of our optimized BFA. Finally, the best threshold is located gradually and quickly by three behaviors of the bacterial swarm, i.e., chemotaxis, and reproduction, elimination and dispersal. Experimental results show that the proposed method is superior to some segmentation methods based on the Genetic Algorithm (GA) and Artificial Fish Swarm Algorithm (AFSA) in convergence, stability and segmentation effects.

Key words: image segmentation, bacterial foraging algorithm, global optimization, SAR image


  • TP391.41,N941.5