改进蚁群优化算法的图像边缘检测

Image edge detection based on improved ant colony optimization algorithm

为了解决图像边缘检测中的噪声问题,并提升检测效率与检测效果,提出改进蚁群优化算法的图像边缘检测方法。所提方法改进了传统蚁群优化算法直接在像素域进行迭代的边缘检测过程,其将蚂蚁分为探测蚁和寻路蚁,寻路蚁采用数据结构控制思想在原图像上随机选择迭代路线,根据蚂蚁移动角度设置像素点结构搜索路线,在所经过的每个像素点上进行附近像素点结构搜索,快速获取整体图像边缘检测信息,再利用探测蚁将寻路蚁给出的结果进行蚂蚁外激素检测,完成对检测效率与检测效果的改进。实验结果证明,相比传统蚁群优化算法,改进蚁群优化算法在图像边缘检测的效率与效果上均有很大提高。

In order to eliminate the noise existing in image edge detection,and improve the detection efficiency and detection effect,an image edge detection method based on improved ant colony optimization algorithm is proposed.The method improves the traditional ant colony optimization algorithm to iterate the process of edge detection directly in pixel domain,and divides the ants into the detection ants and route-finding ants.The route-finding ants based on the data structure control thought are used to select the iterative path randomly on the original image,set the structural search path of the pixel point according to ants moving angle,search the structure of the neighborhood pixel points from each pixel passing by,and obtain the edge detection information of the whole image.The detection ants are used to detect the ant ectohormone according to the results given by routefinding ants to improve the detection efficiency and detection effect.The experimental results show that,in comparison with the traditional ant colony optimization algorithm,the improved ant colony optimization algorithm has a great improvement in the image edge detection efficiency and effect.