首页 | 本学科首页   官方微博 | 高级检索  
     

微粒群优化和区域生长结合的图像分割方法
引用本文:黄力明.微粒群优化和区域生长结合的图像分割方法[J].计算机工程与应用,2009,45(28):193-195.
作者姓名:黄力明
作者单位:镇江高等专科学校 电子信息系,江苏 镇江 212003
摘    要:提出了一种基于微粒群算法的区域生长图像分割方法,该方法利用微粒群较强的搜索能力搜索像素种子点。由于搜索像素种子点是按密度进行,计算量小,大幅度提高了算法的计算速度,同时克服了传统区域生长方法不能自动选择种子且容易导致过分割的局限性。实验表明,该方法可以准确地分割出目标,是一种有效的图像分割方法。

关 键 词:图像分割  区域生长  种子  微粒群优化算法
收稿时间:2009-3-3
修稿时间:2009-5-25  

Region growing method of image segmentation based On Particle Swarm Optimization
HUANG Li-ming.Region growing method of image segmentation based On Particle Swarm Optimization[J].Computer Engineering and Applications,2009,45(28):193-195.
Authors:HUANG Li-ming
Affiliation:Department of Electronics and Information,Zhenjiang College,Zhenjiang,Jiangsu 212003,China
Abstract:A new region growing algorithm for image segmentation is proposed,which is based on Particle Swarm Optimization algorithm by utilizing particle swarm’s power searching ability to search pixel seeds.Because searching pixel seeds are based on density and the computational load is small,the computing speed of the algorithm can be improved obviously.Compared to traditional RG method,the proposed algorithm can overcome the disadvantages that traditional RG method can’t select seeds automatically and leads to over-segment.The results indicate that the algorithm can segment the image accurately and precisely.
Keywords:image segmentation  region growing  seed  particle swarm optimization algorithm
本文献已被 维普 万方数据 等数据库收录!
点击此处可从《计算机工程与应用》浏览原始摘要信息
点击此处可从《计算机工程与应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号