• DocumentCode
    1589677
  • Title

    Visual Location System for Placement Machine Based on Machine Vision

  • Author

    WEI, Luosi ; Jiao, Zongxia

  • Author_Institution
    Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing
  • fYear
    2008
  • Firstpage
    141
  • Lastpage
    146
  • Abstract
    Placement machine is the most critical equipment of SMT (surface mount technology). Using visual location technology in its pick and place process can offer a high speed and precision component placement. This paper presents a visual location system based on machine vision for the placement machine. It begins with an introduction of placement machine and then describes the design and implementation of the visual location system. In the system, two key techniques are completed by secondary development based on VisionPro. One is accurate image location that is solved by the pattern-based location algorithms of PatMax. The other one, camera calibration, is achieved by image warping technology through the checkerboard plate. Moreover, this system can give good performances such as high image locating accuracy with 1/40 sub-pixels, high anti-jamming, and high-speed location of objects whose appearance is rotated, scaled, and/or stretched.
  • Keywords
    automatic optical inspection; computer vision; integrated circuit manufacture; machine tools; production engineering computing; surface mount technology; PatMax; camera calibration; checkerboard plate; image location; image warping; machine vision; pattern-based location algorithms; placement machine; surface mount technology; visual location system; Automation; Calibration; Cameras; Charge coupled devices; Charge-coupled image sensors; Costs; Embedded computing; Machine vision; Sliding mode control; Surface-mount technology; Machine Vision; Placement Machine; VisionPro; Visual Location;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Embedded Computing, 2008. SEC '08. Fifth IEEE International Symposium on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-0-7695-3348-3
  • Type

    conf

  • DOI
    10.1109/SEC.2008.41
  • Filename
    4690739