Image Segmentation Based on Ant Colony Optimization and K -Means Clustering
According to the characteristics of the ant colony optimization and the K -means clustering,a method for the image segmentation based on the ant colony optimization and the K - means clustering was proposed in this paper.Firstly,the basic principle of the two algorithms were introduced.Secondly,their characteristics on the image segmentation were analyzed.Finally the improved algorithm was proposed,this algorithm can effectively overcome shortages which are the slow rate of the ant colony optimization and the K -means clustering dependent on the initial clustering centers.Experimental results proved that the improved algorithm was an effective method for the image segmentation in the practical application,which could segment the object accurately.
Ant colony optimization K-means clustering Image segmentation
Bo Zhao Zhongxiang Zhu Enrong Mao Zhenghe Song
College of Engineering China Agricultural University Beijing,China
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18(万方平台首次上网日期,不代表论文的发表时间)