[1]彭刚,熊超,夏成林,等.一种基于Mark点的点胶机器人视觉目标定位方法[J].智能系统学报,2018,13(05):728-733.[doi:10.11992/tis.201705010]
 PENG Gang,XIONG Chao,XIA Chenglin,et al.A method of vision target localization for dispensing robot based on mark point[J].CAAI Transactions on Intelligent Systems,2018,13(05):728-733.[doi:10.11992/tis.201705010]
点击复制

一种基于Mark点的点胶机器人视觉目标定位方法(/HTML)
分享到:

《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第13卷
期数:
2018年05期
页码:
728-733
栏目:
出版日期:
2018-09-05

文章信息/Info

Title:
A method of vision target localization for dispensing robot based on mark point
作者:
彭刚12 熊超12 夏成林2 林斌3
1. 华中科技大学 自动化学院, 湖北 武汉 430074;
2. 华中科技大学 图像信息处理与智能控制教育部重点实验室, 湖北 武汉 430074;
3. 深圳市海思科自动化技术有限公司, 广东 深圳 518109
Author(s):
PENG Gang12 XIONG Chao12 XIA Chenglin2 LIN Bin3
1. School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;
2. Key Laboratory of Image Processing and Intelligent Control of Education Ministry, Huazhong University of Science and Technology, Wuhan 430074, China;
3.
关键词:
PCB点胶机器人Mark点辅助视觉定位几何特征改进型模板匹配不变性
Keywords:
PCBdispensing robotMark pointassistantvisual localizationgeometric featuresimproved template matchinginvariance
分类号:
TP242
DOI:
10.11992/tis.201705010
摘要:
针对工业生产中PCB点胶机器人的视觉定位问题,提出了一种基于Mark点辅助的视觉定位算法。分析了传统模板匹配、Sift、Surf等算法在Mark点识别与定位中的不足,同时考虑到Mark点所具有的规则几何特征以及算法对于实时性的要求,提出了一种基于Mark点几何特征的改进型模板匹配算法。实验结果表明,这种基于Mark点几何特征的改进型模板匹配算法具有良好的平移、缩放、旋转不变性,能够准确识别并定位Mark点,从而实现对PCB上相关点胶目标点的定位,并满足工程可靠性和实时性的要求。
Abstract:
To address the problem of visual localization of polychlorinated biphenyl (PCB)-dispensing robots in industrial production, a visual localization algorithm based on mark point is proposed in this paper. The results of traditional template matching, Sift and Surf algorithms, were compared and it was found that these algorithms are inadequate for the identification and location of Mark point. Meanwhile, the geometry features of the Mark point and the real-time requirements of the algorithm were considered so that an improved template-matching algorithm based on Mark point geometry features was realized. Experimental results show that this improved template-matching algorithm based on Mark point geometry features can keep good invariance under translation, scale, and rotation, which can accurately identify and locate the mark points, and then indirectly locate the PCB target points while satisfying engineering reliability and real-time constraints.

参考文献/References:

[1] 陈戈珩, 李华杰, 房晓伟. 基于相位一致性和Hough圆的贴片机视觉定位系统的研究[J]. 科学技术与工程, 2015, 15(27):59-63 CHEN Geheng, LI Huajie, FANG Xiaowei. Research of the vision positioning system of surface mounting machine based on phase congruence and Hough circle transform[J]. Science technology and engineering, 2015, 15(27):59-63
[2] JIANG Lianyuan. Efficient randomized Hough transform for circle detection using novel probability sampling and feature points[J]. Optik-international journal for light and electron optics, 2012, 123(20):1834-1840.
[3] JAIN N, JAIN N. Coin recognition using circular Hough transform[J]. International journal of electronics communication and computer technology, 2012, 2(3):101-104.
[4] 刘柏江, 姜明新. 基于sift特征的图像匹配算法[J]. 信息系统工程, 2011(5):34-36, 41.
[5] PANG Yanwei, LI Wei, YUAN Yuan, et al. Fully affine invariant SURF for image matching[J]. Neurocomputing, 2012, 85:6-10.
[6] YIN Hongpeng, PENG Chao, CHAI Yi, et al. A Robust object tracking algorithm based on surf and Kalman filter[J]. Intelligent automation & soft computing, 2013, 19(4):567-579.
[7] 王海波, 周浩, 柳宁. 基于Radon变换的高精度Mark点圆定位算法的改进[J]. 机电工程技术, 2015, 44(7):78-80 WANG Haibo, ZHOU Hao, LIU Ning. The improvement algorithm of high precision mark points detecting circle location based on Radon transform[J]. Mechanical & electrical engineering technology, 2015, 44(7):78-80
[8] ZOU Mingming, LU Di. Recognition algorithm of car license plate characters based on modified template match[J]. Foreign electronic measurement technology, 2010, 29(1):59-61, 80.
[9] CHIDAMBARAM C, LOPES H S. An improved artificial bee colony algorithm for the object recognition problem in complex digital images using template matching[J]. International journal of natural computing research, 2017, 1(2):54-70.
[10] 吴晓军, 邹广华. 基于边缘几何特征的高性能模板匹配算法[J]. 仪器仪表学报, 2013, 34(7):1462-1469 WU Xiaojun, ZOU Guanghua. High performance template matching algorithm based on edge geometric features[J]. Chinese journal of scientific instrument, 2013, 34(7):1462-1469
[11] ZHANG Sen, ZHOU Yongquan. Template matching using grey wolf optimizer with lateral inhibition[J]. Optik-international journal for light and electron optics, 2017, 130:1229-1243.
[12] 田文利. 基于双重滤波与锐化的遥感图像增强算法[J]. 国外电子测量技术, 2017, 36(4):13-16 TIAN Wenli. Remote sense image enhancement algorithm based on filtering and sharpening[J]. Foreign electronic measurement technology, 2017, 36(4):13-16
[13] COMTE F, CUENOD C A, PENSKY M, et al. Laplace deconvolution and its application to dynamic contrast enhanced imaging[J]. arXiv preprint arXiv:1207.2231, 2012.
[14] WANG Yinggui, YANG Le, TANG Liang, et al. Enhanced multi-task compressive sensing using Laplace priors and MDL-based task classification[J]. EURASIP journal on advances in signal processing, 2013, 2013:1-17.
[15] 李均利, 魏平, 陈刚. 一种新颖的医学图像锐化增强算法[J]. 计算机工程与应用, 2008, 44(10):160-162 LI Junli, WEI Ping, CHEN Gang. Novel method for medical image sharpening[J]. Computer engineering and applications, 2008, 44(10):160-162
[16] ZHOU Bin, ZHANG Xiongwei, ZOU Xia, et al. Speech enhancement by short-time spectrum estimation with multivariate Laplace speech model[J]. Przeglad elektrotechniczny, 2012, 88(12):338-342.
[17] 邹滨, 刘翱. 轮廓波变换与改进MSRCR的图像增强[J]. 计算机工程与设计, 2016, 37(6):1560-1566 ZOU Bin, LIU Ao. Image enhancement based on contourlet transform and improved MSRCR[J]. Computer engineering and design, 2016, 37(6):1560-1566
[18] 贾海鹏, 张云泉, 龙国平, 等. 基于OpenCL的拉普拉斯图像增强算法优化研究[J]. 计算机科学, 2012, 39(5):271-277. JIA Haipeng, ZHANG Yunquan, LONG Guoping, et al. Reasearch on laplace image enhancement algorithm optimization based on OpenCL[J]. Computer science, 2012, 39(5):271-277.
[19] DJEKOUNE A O, MESSAOUDI K, AMARA K. Incremental circle hough transform:an improved method for circle detection[J]. Optik-international journal for light and electron optics, 2017, 133:17-31.
[20] 段黎明, 汪威, 张霞. 改进的Hough变换实现圆检测[J]. 计算机集成制造系统, 2013, 19(9):2148-2152 DUAN Liming, WANG Wei, ZHANG Xia. Circle detection through improved hough transform[J]. Computer integrated manufacturing systems, 2013, 19(9):2148-2152

备注/Memo

备注/Memo:
收稿日期:2017-05-09。
基金项目:2016年深圳市科技计划项目(CYZZ20160412111639184).
作者简介:彭刚,男,1973年生,副教授,博士,主要研究方向为机器人与智能制造、嵌入式系统与软件开发、生产制造执行系统。获发明专利3项、实用新型专利4项、外观设计1项、软件著作权3项,获湖北省自然科学奖三等奖1项。发表学术论文40余篇,被SCI收录2篇,EI收录20余篇;熊超,男,1992年生,硕士研究生,主要研究方向为机器人与智能制造、嵌入式系统与软件开发;夏成林,男,1990年生,硕士研究生,主要研究方向为机器人与智能制造、嵌入式系统与软件开发。
通讯作者:彭刚.E-mail:penggang@hust.edu.cn.
更新日期/Last Update: 2018-10-25