Fast 2.5D Model Reconstruction of Assembled Parts with High Occlusion for Completeness Inspection
In this work a dual laser triangulation system is presented for fast building of 2.5D textured models of objects within a production line. This scanner is designed to produce data suitable for 3D completeness inspection algorithms. For this purpose two laser projectors have been used in order to considerably reduce the problem of occlusions in the camera movement direction. Results of reconstruction of electronic boards are presented, together with a comparison with a commercial system.
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motion under varying illumination: unifying structure from motion,
photometric stereo, and multi-view stereo. In Proceedings of the 9th
IEEE International Conference on Computer Vision (ICCV 2003), Nice,
France. Pages 618-625.
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inspection of complex geometry parts using a novel laser
triangulation sensor and a robot. Sensors, Vol. 11, No. 1. (23 December
2010), pp. 90-110.
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based on stereo vision and laser triangulation. Journal on Machine Vision
and Applications (2010). Volume: 21, issue: 3, publisher: Springer,
pages 341-350.
[10] S. Gao, M. Zhao, L. Zhang, and Y. Zou, Dual-beam structured light
vision system for 3D coordinates measurement. In Proceedings of the
7th World Congress on Intelligent Control and Automation (2008),
Chongqing, China.
[11] A. Peiravi, and B. Taabbodi, A reliable 3D laser triangulation-based
scanner with a new simple but accurate procedure for finding scanner
parameters. In Journal of American Science 2010;6(5), 2010.
[12] J. Park, G. N. Desouza, and A. C. Kak, Dual-beam structured-light scanning
for 3-D object modeling. In Proceedings of the 3rd International
Conference on 3-D Digital Imaging and Modeling (2001).
[13] Z. Zhang, Flexible camera calibration by viewing a plane from unknown
orientations. In Proceedings of IEEE International Conference on Computer
Vision, 1999 (ICCV-99), Kerkyra, Greece. Pages 666-673.
[14] J. Heikkil¨a, and O. Silven, A four-step camera calibration procedure
with implicit image correction. In Proceedings of IEEE Computer
Society Conference on Computer Vision and Pattern Recognition 1997
(CVPR-97), San Juan, Puerto Rico. Page 1106.
[15] M. A. Fischler, and R. C. Bolles, Random sample consensus: a paradigm
for model fitting with applications to image analysis and automated
cartography . In Communication of ACM, Volume: 24, Issue: 6, Pages:
381-395, 1981.
[16] J. Molleda, R. Usamentiaga, D. F. Garcia, and F. G. Bulnes, Real-time
flatness inspection of rolled products based on optical laser triangulation
and three-dimensional surface reconstruction. Journal of Electronic
Imaging 19(3), 031206 (Jul-Sep 2010).
[17] Z. Zhang, Iterative point matching for registration of free-form curves.
In International Journal of Computer Vision, Volume 13 Issue 2, Oct.
1994.
[1] W. E. Singhose, W. P. Seering, and N. C. Singer, The effect of input
shaping on coordinate measuring machine repeatability. In Proceedings
of the 1995 IFToMM World Congress on the Theory of Machines and
Mechanisms. Pages 2930-2934.
[2] Q. Zheng, and R. Chellappa, Estimation of illuminant direction, albedo,
and shape from shading. In Proceedings of IEEE Conference on Computer
Vision and Pattern Recognition 1991 (CVPR-91), Maui, HI, USA.
Pages 540-545.
[3] L. Zhang, B. Curless, A. Hertzmann, and S. M. Seitz, Shape and
motion under varying illumination: unifying structure from motion,
photometric stereo, and multi-view stereo. In Proceedings of the 9th
IEEE International Conference on Computer Vision (ICCV 2003), Nice,
France. Pages 618-625.
[4] D. Scharstein, R. Szeliski, and R. Zabih, A taxonomy and evaluation of
dense two-frame stereo correspondence algorithms. In Proceedings of
Stereo and Multi-Baseline Vision 2001 (SMBV 2001), Kauai, HI, USA.
Pages 131-140.
[5] Z. M. Bi, and L. Wang, Advances in 3D data acquisition and processing
for industrial applications. Journal on Robotics and Computer-Integrated
Manufacturing (2010). Volume: 26, issue: 5, publisher: Elsevier. Pages:
403-413.
[6] F. Blais, Review of 20 years of range sensor development. In Journal of
Electronic Imaging, 13(1): 231-240. January 2004.
[7] G. Sansoni, M. Trebeschi, and F. Docchio, State-of-the-art and applications
of 3D imaging sensors in industry, cultural heritage, medicine,
and criminal investigation. Sensors, Volume: 9, Issue: 1, Pages: 568-601,
2009.
[8] F. J. Brosed, J. J. Aguilar, D. Guillomia, and J. Santolaria, 3D geometrical
inspection of complex geometry parts using a novel laser
triangulation sensor and a robot. Sensors, Vol. 11, No. 1. (23 December
2010), pp. 90-110.
[9] J. Vilaca, F. Jaime, and P. Antonio, Non-contact 3D acquisition system
based on stereo vision and laser triangulation. Journal on Machine Vision
and Applications (2010). Volume: 21, issue: 3, publisher: Springer,
pages 341-350.
[10] S. Gao, M. Zhao, L. Zhang, and Y. Zou, Dual-beam structured light
vision system for 3D coordinates measurement. In Proceedings of the
7th World Congress on Intelligent Control and Automation (2008),
Chongqing, China.
[11] A. Peiravi, and B. Taabbodi, A reliable 3D laser triangulation-based
scanner with a new simple but accurate procedure for finding scanner
parameters. In Journal of American Science 2010;6(5), 2010.
[12] J. Park, G. N. Desouza, and A. C. Kak, Dual-beam structured-light scanning
for 3-D object modeling. In Proceedings of the 3rd International
Conference on 3-D Digital Imaging and Modeling (2001).
[13] Z. Zhang, Flexible camera calibration by viewing a plane from unknown
orientations. In Proceedings of IEEE International Conference on Computer
Vision, 1999 (ICCV-99), Kerkyra, Greece. Pages 666-673.
[14] J. Heikkil¨a, and O. Silven, A four-step camera calibration procedure
with implicit image correction. In Proceedings of IEEE Computer
Society Conference on Computer Vision and Pattern Recognition 1997
(CVPR-97), San Juan, Puerto Rico. Page 1106.
[15] M. A. Fischler, and R. C. Bolles, Random sample consensus: a paradigm
for model fitting with applications to image analysis and automated
cartography . In Communication of ACM, Volume: 24, Issue: 6, Pages:
381-395, 1981.
[16] J. Molleda, R. Usamentiaga, D. F. Garcia, and F. G. Bulnes, Real-time
flatness inspection of rolled products based on optical laser triangulation
and three-dimensional surface reconstruction. Journal of Electronic
Imaging 19(3), 031206 (Jul-Sep 2010).
[17] Z. Zhang, Iterative point matching for registration of free-form curves.
In International Journal of Computer Vision, Volume 13 Issue 2, Oct.
1994.
@article{"International Journal of Electrical, Electronic and Communication Sciences:59259", author = "Matteo Munaro and Stefano Michieletto and Edmond So and Daniele Alberton and Emanuele Menegatti", title = "Fast 2.5D Model Reconstruction of Assembled Parts with High Occlusion for Completeness Inspection", abstract = "In this work a dual laser triangulation system is presented for fast building of 2.5D textured models of objects within a production line. This scanner is designed to produce data suitable for 3D completeness inspection algorithms. For this purpose two laser projectors have been used in order to considerably reduce the problem of occlusions in the camera movement direction. Results of reconstruction of electronic boards are presented, together with a comparison with a commercial system.
", keywords = "3D quality inspection, 2.5D reconstruction, laser triangulation, occlusions.", volume = "5", number = "11", pages = "1523-7", }
