首页 | 本学科首页   官方微博 | 高级检索  
     

混沌蚁群算法在图像边缘检测中的应用
引用本文:耿艳香,孙云山,谢靖鹏,刘超.混沌蚁群算法在图像边缘检测中的应用[J].计算机工程与应用,2015,51(2):194-197.
作者姓名:耿艳香  孙云山  谢靖鹏  刘超
作者单位:1.天津商业大学 信息工程学院,天津 300134 2.天津大学 电子信息工程学院,天津 300072
基金项目:国家自然科学基金(No.61340034);中国博士后科学基金(No.2013M530873);天津市应用基础与前沿技术研究计划(No.13JCYBJC15600);天津市高校科技发展基金资助项目(No.20110709)。
摘    要:运用混沌蚁群算法进行图像的边缘检测是针对混沌蚁群算法具有随机性、遍历性、正反馈性,通过更新信息素矩阵来计算图像阈值,从而获得图像边缘信息,能够更全面、迅速地找到图像的边缘,避免过早陷入局部最优,提高了图像边缘检测的连续性和准确性。计算机仿真实验表明,通过混沌蚁群算法获得的图像边缘更加完整和清晰,取得了较好的效果。

关 键 词:混沌蚁群算法  图像分割  边缘检测  

Research on chaotic ant colony algorithm in image edge detec-tion
GENG Yanxiang,SUN Yunshan,XIE Jingpeng,LIU Chao.Research on chaotic ant colony algorithm in image edge detec-tion[J].Computer Engineering and Applications,2015,51(2):194-197.
Authors:GENG Yanxiang  SUN Yunshan  XIE Jingpeng  LIU Chao
Affiliation:1.School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China 2.School of Electric Information Engineering, Tianjin University, Tianjin 300072, China
Abstract:Chaos ant colony algorithm is applied in image edge detection, because of its randomness, ergodicity and positive feedback. The update of the pheromone matrix by chaos ant colony algorithm is used to calculate the threshold to get the edge of image, and then it can fully and quickly find the edge of image to avoid falling into the optimal value. The algorithm improves the continuity and accuracy of image edge detection. Simulation results of the computer show that chaos ant colony algorithm to obtain more completely and clearly edge, which is obtained better effect.
Keywords:chaos ant colony algorithm  image segmentation  edge detection
本文献已被 CNKI 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