摘要
针对工业传输链条在插销装配工艺中位置准度要求,提出了一种基于机器视觉的低成本、低算力、高精度的插销自动调整系统。在图像采集阶段,通过对背景差分算法加入帧数获取约束后有效快速去除干扰背景;在位置获取阶段,对霍夫变换引入粒子群算法加快插销边缘特征定位,并结合最小包围矩计算出插销的角度位置;与其他几种常见匹配算法进行比较,结果表明改进后的方法不仅提高了计算速度,并且能够获得更高的计算精度。
In view of the position accuracy requirement of industrial transmission chain in latch assembly process,a low cost,low computational power and high precision latch automatic adjustment system based on machine vision has thus been proposed.In the image acquisition stage,the interference background is effectively and quickly removed by adding frame number acquisition constraints to the background difference algorithm.In the position acquisition stage,the particle swarm algorithm is introduced into Hough transform to speed up the pin edge feature positioning,with the angular position of the pin calculated by combining the minimum enclosing moment.Compared with other common matching algorithms,the results show that the improved method can not only improve the computational speed but also obtain a higher computational accuracy.
作者
黄佳兴
孙晓
雷张文
于柳
邓林志
HUANG Jiaxing;SUN Xiao;LEI Zhangwen;YU Liu;DENG Linzhi(College of Mechanical Engineering,Hunan University of Technology,Zhuzhou Hunan 412007,China;Zhuzhou Guochuang Rail Technology Co.,Ltd.,Zhuzhou Hunan 412007,China;Library,Hunan University of Technology,Zhuzhou Hunan 412007,China)
出处
《湖南工业大学学报》
2023年第4期42-49,共8页
Journal of Hunan University of Technology
基金
湖南省重点领域研发计划基金资助项目(2022GK2068)
湖南省自然科学基金省市联合基金资助项目(2021JJ50053)。
关键词
机器视觉
图像处理
目标调整
特征拆分
霍夫变换
machine vision
image processing
target adjustment
feature splitting
Hough transform
