中国铁道科学2017，Vol.38Issue(4)：8-14,7.DOI:10.3969/j.issn.1001-4632.2017.04.02
基于优化蚁群算法的钢轨轮廓识别
Rail Profile Identification Based on Optimized Ant Colony Algorithm
摘要
Abstract
Aiming at the existing problems of traditional ant colony algorithm in rail image recognition,the ant colony algorithm is optimized in four aspects.For the optimization of initialization process,the nonlinear iterative equation of one-dimensional Logistic chaotic mapping sequence is adopted to make the initialization distribution of ant colony more uniform,so that a large number of independent operations are avoided.For the optimization of search process,random search strategy is used at the beginning of ant colony search.The threshold is automatically set according to the gray gradient value of the image.The pixels of rail edge in the image are determined preliminarily,and then a region search model is set up to search and depict the rail edge accurately.For the optimization of search step length,in the early stage of the search,large step random search strategy is used to recognize the pixels of rail edge.Then small step region search strategy is used to recognize more accurately the pixels of rail edge so as to realize the accurate recognition of rail profile as well as reduce the search time and the convergence time of the algorithrr.For the optimization of pheromone update strategy,to prevent falling into local optimum,the pheromone is updated according to the maximum and minimum pheromone concentration of the pheromone which is set automatically after each search.A contrast test of track profile recognition for rail images acquired on straight and curve lines is conducted by Canny edge detection operator,traditional and optimization algorithm respectively.Results show that the proposed optimization algorithm has better robustness and higher recognition efficiency.关键词
蚁群算法/钢轨识别/边缘检测/混沌向量/搜索策略/信息素Key words
Ant colony algorithm/Rail identification/Edge detection/Chaos vector/Search strategy/Pheromone分类
交通工程引用本文复制引用
旷文珍,常峰,许丽,李积英..基于优化蚁群算法的钢轨轮廓识别[J].中国铁道科学,2017,38(4):8-14,7.基金项目
中国铁路总公司科技研究开发计划项目(2016X003-H) （2016X003-H）
甘肃省青年科技基金资助项目(1308RJYA096) （1308RJYA096）
