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基于旋转立体视觉的元件针脚精密定位方法 被引量:3

Precise Positioning Method of Electronic-Component Leads Based on Rotational Stereo Vision
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摘要 目前自动插件机大部分采用底部相机的视觉定位方式,常会有元件针脚与本体难以区分的情况.为此文中提出了一种基于旋转立体视觉的元件针脚精密定位方法:首先提出一种利用棋盘格标定板的旋转轴标定方法,进行系统标定;接着获取多个角度元件针脚侧面图像,并提出了一种基于空间矩算法提取元件针脚亚像素特征点的方法;然后优化多个角度图像中的特征点,计算针脚的空间位置.搭建了基于背光源的视觉定位系统进行实验,结果表明:文中方法的针脚定位精度随着成像次数增加而提高并收敛,且元件抓取的位姿对针脚定位精度无影响;与现有定位方法相比,文中方法能更稳定地获取针脚图像,因而能获得更好的定位精度,此外其在飞行中取像的方式也节省了插件机的拍照时间. At present most of the auto-inserting machines adopt the vision positioning method with bottom-camera,but it is difficult for some leads in bottom images of components to be distinguished from the body. In order to improve the positioning reliability,a precise positioning method is proposed of electronic-component leads based on rotational stereo vision. In the proposed method,firstly,a rotational-axis calibration method with checkerboard is put forward,and system calibration is finished. Secondly,side images of the component leads are obtained from multiple angles,a sub-pixel feature point extracted method is proposed on the basis of spatial moment. Then,spatial positioning of leads is calculated by optimizing feature points of multiple images. A vision positioning system with backlight is built for experiment,experimental results show that with the number of images increasing,the accuracy of proposed method increases and converges; grabbing position and angle produce no effect on accuracy of proposed method; the proposed method possesses higher accuracy and is more stable than the traditional method.On the other hand,because images can be obtained when moving,the proposed method brings about higher efficiency than the traditional method.
作者 邝泳聪 李家裕 梁经伦 欧阳高飞 KUANG Yongcong;LI Jiayu;LIANG Jinglun;OUYANG Gaofei(School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 51062;School of Mechanical Engineering , Dongguan University of Technology, Dongguan 523808 , Guangdong , China)
出处 《华南理工大学学报(自然科学版)》 EI CAS CSCD 北大核心 2018年第2期44-52,58,共10页 Journal of South China University of Technology(Natural Science Edition)
基金 广东省自然科学基金资助项目(2015A030310415) 东莞市工业攻关(数控一代)科技计划项目(2015222119)~~
关键词 自动插件机 机器视觉 立体视觉 系统标定 特征提取 auto-inserting machines machine vision stereo vision system calibration feature extraction
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