摘要
传统图像分割算法在精度控制等方面难以满足图像处理识别的要求,导致算法的稳定性较差。为此,提出基于改进蚁群算法的图像轮廓高精度分割算法研究,根据图像轮廓的几何表达式构建高精度分割路径的数学模型;依据改进蚁群算法的优点和蚂蚁路径上遗留的信息素浓度和启发因子,进行反复的迭代寻优,实现对图像轮廓分割的高精度控制。仿真数据表明,所提方法设计的路径最短、迭代次数少、图像轮廓目标点间距控制精度高。
Traditional image segmentation algorithms are difficult to meet the requirements of image processing and recognition in terms of precision control,which leads to poor stability of the algorithm.To this end,a high-precision segmentation algorithm for image contours based on improved ant colony algorithm is proposed,and a mathematical model of high-precision segmentation path is constructed according to the geometric expression of image contour;Based on the advantages of improved ant colony algorithm and the concentration of pheromone left on the path of ants and heuristic factors,iterative optimization is performed repeatedly to achieve high-precision control of image contour segmentation.The simulation data shows that the proposed method has the shortest path,fewer iterations,and high precision in the control of the distance between the target points of the image contour.
作者
李巧兰
卢永祥
卢荣辉
Li Qiaolan;Lu Yongxiang;Lu Ronghui(Information Technology and Laboratory Management Center,Wuyi University,Longyan,Fujian 354300,China)
出处
《黑龙江工业学院学报（综合版）》
2021年第1期47-51,共5页
Journal of Heilongjiang University of Technology(Comprehensive Edition)
基金
2019年福建省中青年教师教育科研项目“基于空间自相关性的图像智能增强研究”(项目编号:JAT190780)。
关键词
图像分割
改进蚁群算法
迭代
轮廓目标点
image segmentation
improved ant colony algorithm
iteration
contour target point
