摘要
将机器视觉技术引入到铁轨扣件缺损的检测中,采用HALCON平台作为扣件图像分析和处理的核心模块,实现了从图像采集、预处理到检测算法,在HALCON环境中利用Canny算子提取扣件边缘.实验结果表明,每幅扣件图像的边缘提取时间均值约为25.7ms,与其他算子相比,利用Canny算子提取扣件边缘的速度较快,可为铁路工作人员维护提供参考依据.
In this paper,the machine vision technology is applied for the detection process of railway fastener,and the image acquisition,pre-processing,edge detection algorithm are realized in HALCON.The experimental results show that the edge extraction time of each fastener image is mean about 25.7 ms.Compared to other operators,using Canny operator to extract the edge of the fastener is faster in HALCON.It may provide reference for the maintenance of railway staff.
出处
《西北师范大学学报（自然科学版）》
CAS
北大核心
2017年第5期45-48,共4页
Journal of Northwest Normal University(Natural Science)
基金
国家自然科学基金资助项目(61461023)
兰州市科技计划资助项目(20141187)
兰州工业学院青年科技创新计划资助项目(14K-010)
关键词
智能交通
边缘检测
CANNY算子
intelligent transportation
edge detection
Canny operator
