Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31742
Fast 2.5D Model Reconstruction of Assembled Parts with High Occlusion for Completeness Inspection

Authors: Matteo Munaro, Stefano Michieletto, Edmond So, Daniele Alberton, Emanuele Menegatti


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.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1336


[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.