Advertisement

Efficient Completeness Inspection Using Real-Time 3D Color Reconstruction with a Dual-Laser Triangulation System

  • Matteo MunaroEmail author
  • Edmond Wai Yan So
  • Stefano Tonello
  • Emanuele Menegatti
Chapter
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Abstract

In this chapter, we present the final system resulting from the European Project “3DComplete” aimed at creating a low-cost and flexible quality inspection system capable of capturing 2.5D color data for completeness inspection. The system uses a single color camera to capture at the same time 3D data with laser triangulation and color texture with a special projector of a narrow line of white light, which are then combined into a color 2.5D model in real time. Many examples of completeness inspection tasks are reported, which are extremely difficult to analyze with the state-of-the-art 2D-based methods. Our system has been integrated into a real production environment, showing that completeness inspection incorporating 3D technology can be readily achieved in a short time at low costs.

Keywords

Point Cloud Conveyor Belt Range Image Depth Resolution Color Scanner 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This research has been funded by the European Unions 7th Framework program managed by REAResearch Executive Agency (http://ec.europa.eu/research/rea—FP7/2007-2013) under Grant Agreement No. 262009, 3D Complete project.

References

  1. 1.
    Bi Z, Wang L (2010) Advances in 3d data acquisition and processing for industrial applications. Robot Comput Integr Manufact 26:403–413CrossRefGoogle Scholar
  2. 2.
    Chen C, Kak A (1987) Modeling and calibration of a structured light scanner for 3-d robot vision. Int Conf Robot Autom 4:807–815Google Scholar
  3. 3.
    Huynh DQ, Owens RA, Hartmann PE (1999) Calibrating a structured light stripe system: a novel approach. Int J Comput Vis 33:73–86CrossRefGoogle Scholar
  4. 4.
    Malamas EN, Petrakis EGM, Zervakis M, Petit L, Legat J-D (2003) A survey on industrial vision systems, applications and tools. Image Vis Comput 21:171–188CrossRefGoogle Scholar
  5. 5.
    McIvor AM (2002) Non-linear calibration of a laser stripe profiler. Opt Eng 41:205CrossRefGoogle Scholar
  6. 6.
    Pears N, Liu Y, Bunting P (eds) (2012) 3D imaging, analysis and applications. Springer, LondonGoogle Scholar
  7. 7.
    Reid ID (1996) Projective calibration of a laser-stripe range finder. Image Vis Comput 14:659–666CrossRefGoogle Scholar
  8. 8.
    So EWY, Munaro M, Michieletto S, Menegatti E, Tonello S (2013) 3d complete: efficient completeness inspection using a 2.5d color scanner. Comput Ind Spec Issue 3D Imaging Ind Elsevier 64(9):1237–1252Google Scholar
  9. 9.
    So EWY, Michieletto S, Menegatti E (2012) Calibration of a dual-laser triangulation system for assembly line completeness inspection. In: IEEE international symposium on robotic and sensors environments, pp 138–143Google Scholar
  10. 10.
    Stocher W, Biegelbauer G (2005) Automated simultaneous calibration of a multi-view laser stripe profiler. In: IEEE international conference on robotics and automation, pp 4424–4429Google Scholar
  11. 11.
    Trucco E, Fisher RB, Fitzgibbon AW, Naidu DK (1998) Calibration, data consistency and model acquisition with laser stripers. Int J Comput Integr Manuf 11:292–310CrossRefGoogle Scholar
  12. 12.
    Vilaça JL, Fonseca JC, Pinho AM (2009) Calibration procedure for 3d measurement systems using two cameras and a laser line. Opt Laser Technol 41:112–119CrossRefGoogle Scholar
  13. 13.
    Yamauchi K, Saito H, Sato Y (2008) Calibration of a structured light system by observing planar object from unknown viewpoints. In: International conference on pattern recognition, pp 1–4Google Scholar
  14. 14.
    Zhou F, Zhang G (2005) Complete calibration of a structured light stripe vision sensor through planar target of unknown orientations. Image Vis Comput 23:59–67CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London (outside the USA) 2015

Authors and Affiliations

  • Matteo Munaro
    • 1
    Email author
  • Edmond Wai Yan So
    • 1
  • Stefano Tonello
    • 2
  • Emanuele Menegatti
    • 1
  1. 1.Intelligent Autonomous Systems LaboratoryUniversity of PadovaPaduaItaly
  2. 2.IT+Robotics SrlPaduaItaly

Personalised recommendations