计算机工程与应用2017，Vol.53Issue(23)：171-176,6.DOI:10.3778/j.issn.1002-8331.1704-0161
基于改进蚁群算法的图像边缘检测研究
Research on image edge detection based on improved ant colony algorithm
摘要
Abstract
There are some questions that the edge is unsmooth, the noise is affected greatly, and it is easy to converge to local, when the traditional ant colony algorithm is used in edge detection. In order to improve the quality of edge detection, firstly, the algorithm in this paper determines the initial position and the heuristic matrix by combining the method of the gray gradient and the region gray mean; secondly, the weight factor is introduced to define the new probability transfer function, and the pheromone matrix is updated by the chaos algorithm and adaptive parameters. The experimental results show that the improved ant colony algorithm can effectively reduce the influence of noise on edge detection, and detect image edge that is more complete and clear.关键词
蚁群算法/边缘检测/权重/梯度/区域灰度均值/自适应Key words
ant colony algorithm/edge detection/weight/gradient/region gray mean/adaptive分类
信息技术与安全科学引用本文复制引用
汪凯,张贵仓..基于改进蚁群算法的图像边缘检测研究[J].计算机工程与应用,2017,53(23):171-176,6.基金项目
甘肃省科技计划资助(No.17YF1FA119). （No.17YF1FA119）
