期刊文献+

基于视觉的贴片元件检测算法 被引量:3

Vision-Based Inspection Algorithm for Chip Components
下载PDF
导出
摘要 为了实现贴片元件的自动检测,提出了一种基于视觉的贴片元件几何特征参数检测方法.首先采用最大外接矩形法实现元件的粗定位及确定边缘的分割点,并采用Canny和Zernike矩边缘检测算子实现边缘的精确定位.然后,利用分割点将边缘分割成4部分,分别进行直线和圆弧拟合,得到其精确值.同时,利用快速傅里叶变换后的图像特征,实现端面图像中条纹方向的判定.实验中测得亚像素边缘点的定位精度为0.03像素,直线拟合精度为0.03像素,圆弧拟合精度为0.05像素,端面条纹判断的准确率为100%.实验结果表明:文中提出的检测方法能很好地满足贴片元件自动视觉检测稳定可靠、精度高及实时性强的要求. In order to automatically inspect chip components, a vision-based method is proposed to calculate the geometrical parameters of the components. In this method, first, the coarse location of chip components and the edge point sorting are realized by means of the maximum external rectangle method, and the precise location of the edge is implemented by using the Canny operator and the Zernike moment operator. Next, the edge points are sorted into 4 parts according to sorting points, which are then fitted respectively via line and arc fittings to obtain the corresponding accurate values. Moreover, the stripe direction of the transverse image of chip components is correctly judged according to the image characteristics obtained via the fast Fourier transform (FFT). Finally, an experiment is carried out, with a subpixel location precision of 0.03 pixel, a line fitting precision of O. 03 pixel, an arc fitting precision of 0. 05 pixel and a stripe direction accuracy of the transverse image of 100% being obtained. The results indicate that the proposed inspection method is of strong stability, high precision and excellent real-time perfor- mance, which is helpful in the automatic Vision-based inspection of chip components.
出处 《华南理工大学学报(自然科学版)》 EI CAS CSCD 北大核心 2010年第1期65-69,86,共6页 Journal of South China University of Technology(Natural Science Edition)
基金 中国博士后科学基金资助项目(20070420784) 广东省自然科学基金博士科研启动项目(8451064101000594) 广东省工业攻关项目(2008B01040004)
关键词 贴片元件 亚像素 视觉检测 快速傅里叶变换 边缘检测 拟合 chip component subpixel vision inspection fast Fourier transform edge detection fitting
  • 相关文献

参考文献11

  • 1胡跃明,杜娟,吴忻生,袁鹏,戚其丰,林伟强,梁耀国.基于视觉的高速高精度贴片机系统的程序实现[J].计算机集成制造系统-CIMS,2003,9(9):760-764. 被引量:32
  • 2Koh K C, Ko K W, Choi B W,et al. An automatic inspection of SMT rectangular chips based on PCA algorithm [ C] //Proceedings of Machine Vision and Its Optomechatronic Applications. Bellingham : SPIE ,2004:208-214.
  • 3Acciani G, Brunetti G, Fornarelli G. Application of neural networks in optical inspection and classification of solder joints in surface mount technology [ J ]. IEEE Transactions on Industrial Informatics ,2006,2( 3 ) :200-209.
  • 4张舞杰,杨义禄,李迪,叶峰.自动影像测量系统关键算法[J].光学精密工程,2007,15(2):294-301. 被引量:48
  • 5张舞杰,李迪,叶峰.基于计算机视觉技术的微钻刃面自动光学检测[J].华南理工大学学报(自然科学版),2006,34(11):55-59. 被引量:14
  • 6Canny J. A computational approach to edge detection [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986,8 (6) :679-698.
  • 7Qu Y D, Cui C S, Chen S B, et al. A fast subpixel edge detection method using Sobel-Zernike moments operators [J]. Image and Vision Computing,2005,23( 1): 11-17.
  • 8Tian Q C, Pan Q, Cheng Y M, et al. Fast algorithm and application of Hough transform in iris segmentation [ C ]// Proceedings of IEEE International Conference on Machine Learning and Cybernetics. Shanghai : IEEE, 2004 : 3 977- 3 980.
  • 9Cha J, Cofer R H, Kozaitis S P. Extended Hough transform for linear feature detection [ J ]. Pattern Recognition ,2006,39 (6) : 1034-1043.
  • 10Shapiro V. Accuracy of the straight line Hough transform : the non-voting approach [ J ]. Computer Vision and Image Understanding,2006,103 ( 1 ) : 1-21.

二级参考文献32

  • 1郭强生,靳卫国,周庆亚.集成电路粘片机视觉检测技术研究[J].电子工业专用设备,2005,34(7):34-40. 被引量:18
  • 2邹定海,叶声华,王春和,郭育.用于在线测量的视觉检测系统[J].仪器仪表学报,1995,16(4):337-341. 被引量:35
  • 3吴晓波,安文斗,杨钢.图像测量系统中的误差分析及提高测量精度的途径[J].光学精密工程,1997,5(1):133-144. 被引量:51
  • 4DAVITT E,STAM F A, BARRETT J. The effect of power cycling on the reliability of a head-free surface mount assemblies[J]. IEEE Trans on Components and Packaging Technologies, 2001,24 (2) :241-249.
  • 5LEE W S, LEE S H,LEE Y D, LEE B H. Improving the productivity of a multi- head surface mounting machine with genetic algorithms[A]. IEEE Int Conf on Intelligent Robotsand Systems[C]. IEEE,1999. 1780-1785.
  • 6FISHER E, HINER J B, DIXON D. SMT adhensive deposition: the line to success[J]. SMT Surface Mount Technology Magazine, 2000, 14 (12): 152-156.
  • 7Hecht O,Dishon G.Automatic optical inspection (AOI)[C]// Proc Electronic Compon Conf.Las Vegas,NV:IEEE,1990:659-661.
  • 8Hong Ji-joong,Park Kyung-ja,Kim Kyung-gu.Parallel processing machine vision system for bare PCB inspection[C]// Proc Industrial Electronics Society conference.Aachen:IEEE Industrial Electronics Society Press,1998:1346-1350.
  • 9Scaman M E,Economikos L.Computer vision for automatic inspection of complex metal patterns on multichip modules (MCM-D)[J].IEEE Trans on Components,Packaging,and Manufacturing Technology,Part B:Advanced Packaging,1995,18(4):675-684.
  • 10Seaman M E,Economikos L,Lambright J.Computer vision for automatic inspection of a high density grid of pads on multi-chip modules (MCM-D)[J].IEEE Trans on Components,Packaging,and Manufacturing Technology,Part B:Advanced Packaging,1994,17 (3):291-299.

共引文献86

同被引文献32

引证文献3

二级引证文献15

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部