Fuzzy clustering analysis based on ant colony algorithm for image edge detection
A fuzzy clustering method based on ant colony algorithm is presented to solve fuzzy edge detection problems in image processing. Based on traditional fuzzy clustering method (FCM), this method uses the ability of ant colony algorithm for disposing local extremum firstly to overcome sensitivity of FCM to initialization, making the numbers of clustering as well as the center of clustering dynamically confirmed. And then the results for fuzzy clustering method can be used to combine fuzzy clustering algorithm (FCM) to make up the deficiency of ant colony algorithm and to get a better global searching capability. The results showed that the method of fuzzy clustering method based on ant colony algorithm can not only detect the fuzzy edge and exiguous edge correctly, but also improve the searching efficiency.
ant colony algorithm fuzzy clustering algorithm image edge detection
CHENG Man ZHANG Shuguang YUAN Hongbo GAO Liai
Mechanical and electricity of College Agriculture university of Hebei , Baoding , 071001
国际会议
北京
英文
2007-08-05（万方平台首次上网日期，不代表论文的发表时间）