Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Multi-facet 3D Scanner Based on Stripe Laser Light Image

선형 레이저 광 영상기반 다면 3 차원 스캐너

  • Ko, Young-Jun (Dept. of Electrical and Information Engineering, Seoul National University of Science and Technology) ;
  • Yi, Soo-Yeong (Dept. of Electrical and Information Engineering, Seoul National University of Science and Technology)
  • 고영준 (서울과학기술대학교 전기정보공학과) ;
  • 이수영 (서울과학기술대학교 전기정보공학과)
  • Received : 2016.06.08
  • Accepted : 2016.08.17
  • Published : 2016.10.01
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Abstract

In light of recently developed 3D printers for rapid prototyping, there is increasing attention on the 3D scanner as a 3D data acquisition system for an existing object. This paper presents a prototypical 3D scanner based on a striped laser light image. In order to solve the problem of shadowy areas, the proposed 3D scanner has two cameras with one laser light source. By using a horizontal rotation table and a rotational arm rotating about the latitudinal axis, the scanner is able to scan in all directions. To remove an additional optical filter for laser light pixel extraction of an image, we have adopted a differential image method with laser light modulation. Experimental results show that the scanner's 3D data acquisition performance exhibited less than 0.2 mm of measurement error. Therefore, this scanner has proven that it is possible to reconstruct an object's 3D surface from point cloud data using a 3D scanner, enabling reproduction of the object using a commercially available 3D printer.

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References

  1. D. Flack, "Good practice guide no. 43 CMM probing," National Physical Laboratory, pp. 6-11, 2014
  2. J. Gu and D. Kim, "Measurement of weak forces in atomic force microscopy," Journal of the Korean Society of Precision Engineering, vol. 19, no. 3, 2002.
  3. C. Chu, J. Bak, H. Kim, J. Bak, and S. Lim, "Recent trends of 3D reconstruction technology," Electronics and Telecommunications Trends, vol. 22, no. 4, 2007.
  4. S. Baek and S. Bak, "Shape measurement by using opical triangulation," Journal of the Korean Society of Precision Engineering, vol. 22, no. 4, 2005.
  5. R. Jain, R. Kasturi, B. G. Schunck, Machine Vision, McGraw-Hill, 1995.
  6. J. Posdamer and M. Altschuler, "Surface measurement by space-encoded projected beam system," Computer Graphics and Image Processing, vol. 18, pp. 1-17, 1982. https://doi.org/10.1016/0146-664X(82)90096-X
  7. D. Scharstein and R. Szeliski, "High accuracy stereo depth maps using structured light," Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 195-202, 2003.
  8. P. Cignoni, M. Callieri, M. Corsini, M. Dellenpiane, F. Ganovelli, and G. Ranzuglia, "Meshlab: An open-source mesh processing tool," Eurographics Italian Chapter Conference, pp. 129-136, 2008.
  9. http://withrobot.com/.
  10. S. Zhang and P. Huang, "Novel method for structured light system calibration," Optical Engineering, vol. 45, no. 8, pp. 083601-083608, 2006. https://doi.org/10.1117/1.2336196
  11. http://www.vision.caltech.edu/bouguetj/calib_doc/.
  12. M. Kazhdan, M. Bolitho, and H. Hoppe, "Poisson surface reconstruction," Eurographics Symposium on Geometry Processing, 2006.
  13. http://store.makerbot.com/digitizer.html.
  14. https://matterandform.net/scanner.
  15. Y. Ko, S. Yi, and J. Lee, "Development of 3D scanner based on laser structured-light image," Journal of Institute of Control, Robotics and Systems, vol. 22, no. 3, pp. 186-191, 2016. https://doi.org/10.5302/J.ICROS.2016.15.0204