基于遗传蚁群算法在图像边缘检测中的研究  

Research on image edge detection based on genetic ant colony algorithm

作　　者：何小虎[1] HE Xiao-hu(School of Network Security and Information Technology,Weinan Normal University,Weinan 714099,Shaanxi Province,China)

机构地区：[1]渭南师范学院网络安全与信息化学院,陕西渭南714099

出　　处：《信息技术》2018年第9期75-78,共4页Information Technology

基　　金：陕西军民融合研究基金项目(17JMR28);陕西教育厅科研计划项目(17JK0267;17JK0278);渭南师范学院自然科学研究项目(17YKS13)

摘　　要：文中根据蚁群算法和遗传算法各自的优点,对两个算法进行有效的融合,提出了一种优化的遗传蚁群图像边缘检测算法。通过对遗传算法中选择、交叉、变异算子和进化淘汰机制的改进,把搜索的优质解转化为蚁群算法信息素初始值,并对蚁群算法的转移规则、信息素浓度更新机制进行改进。通过仿真实验表明,该算法可以更好地检测出图像的边缘,而且算法的运行效率也提高了15%。According to the respective advantages of ant colony algorithm and genetic algorithm,two algorithms are effectively fused,and an optimized genetic ant colony image edge detection algorithm is proposed. Through the improvement of selection, crossover, mutation operator and evolutionary elimination mechanism in genetic algorithm,the high quality solution of search is transformed into initial value of pheromone in ant colony algorithm,and the transfer rule and pheromone concentration update mechanism of ant colony algorithm are improved. The simulation experiment shows that the algorithm can detect the edge of the image better,and the efficiency of the algorithm is also improved by 15%.

关 键 词：边缘检测 遗传蚁群算法 转移规则 信息素 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]