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Defect Detection in Furniture Elements with the Hough Transform Applied to 3D Data

  • Leszek J Chmielewski
  • Katarzyna Laszewicz-Śmietańska
  • Piotr Mitas
  • Arkadiusz Orłowski
  • Jarosław Górski
  • Grzegorz Gawdzik
  • Maciej Janowicz
  • Jacek Wilkowski
  • Piotr Podziewski
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 403)

Abstract

Defects in furniture elements were detected using data from a commercially available structured light 3D scanner. Out-of-plane deviations down to 0.15 mm were analyzed successfully. The hierarchical, iterated version of the Hough transform was used. The calculation of position of the plane could be separated from that of its direction due to the assumption of nearly horizontal location of the plane, which is natural when the tested elements lie on a horizontal surface.

Keywords

Defect detection Quality inspection Furniture elements Iterated Hierarchical Hough transform 3D scanner Structured light 

References

  1. 1.
    Young, T., Winistorfer, P., Siqun, W.: Multivariate control charts of MDF and OSB vertical density profile attributes. For. Prod. J. 49(5), 79–86 (1999)Google Scholar
  2. 2.
    Zakrzewski, W., Staniszewska, A.: Accuracy of Woodwork Cutting (in Polish). Wydaw. Akademii Rolniczej im. Augusta Cieszkowskiego, Poznań (2002)Google Scholar
  3. 3.
    Lăzărescu, C.N., Lăzărescu, C.: Tolerances and Dimensional Control in Wood Industry. Editura Universităţii Transilvania, Braşov (2005)zbMATHGoogle Scholar
  4. 4.
    Laszewicz, K., Górski, J.: Control charts as a tool for the management of dimensional accuracy of mechanical wood processing (in Russian). Ann. Wars. Univ. Life Sci.-SGGW, For. Wood Technol 65, 88–92 (2008)Google Scholar
  5. 5.
    Laszewicz, K.: Machining Accuracy of MDF Boards Milling Process (in Polish). Ph.D. thesis. Warsaw University of Life Sciences, Faculty of Wood Technology, Warsaw (2011)Google Scholar
  6. 6.
    Laszewicz, K., Górski, J., Wilkowski, J.: Long-term accuracy of MDF milling process-development of adaptive control system corresponding to progression of tool wear. Eur. J. Wood Wood Prod. 71(3), 383–385 (2013). doi: 10.1007/s00107-013-0679-2 CrossRefGoogle Scholar
  7. 7.
    Innovativ vision: woodeye. http://woodeye.se/en/ (2015). Accessed 09 Mar 2015
  8. 8.
    WEINING: company. http://www.weinig.com (2015). Accessed 09 Mar 2015
  9. 9.
    MiCROTEC: company. http://www.microtec.eu (2015). Accessed 09 Mar 2015
  10. 10.
    Bucur, V.: Techniques for high resolution imaging of wood structure: a review. Meas. Sci. Technol. 14(12), R91 (2003). doi: 10.1088/0957-0233/14/12/R01 CrossRefGoogle Scholar
  11. 11.
    Longuetaud, F., Mothe, F., Kerautret, B., Krähenbühl, A., Hory, L., Leban, J., Debled-Rennesson, I.: Automatic knot detection and measurements from X-ray CT images of wood: a review and validation of an improved algorithm on softwood samples. Comput. Electron. Agric. 85, 77–89 (2012). doi: 10.1016/j.compag.2012.03.013 CrossRefGoogle Scholar
  12. 12.
    Tarsha-Kurdi, F., Grussenmeyer, P.: Hough-transform and extended RANSAC algorithms for automatic detection of 3D building roof planes from Lidar data. In: Proceedings of the ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007. vol. XXXVI-3/W52., Espoo, Finland, pp. 407–412 (Sep 2007)Google Scholar
  13. 13.
    Borrmann, D., Elseberg, J., Lingemann, K., Nüchter, A.: The 3D hough transform for plane detection in point clouds: a review and a new accumulator design. 3D Res. 2(2), 1–13 (2011). doi: 10.1007/3DRes.02(2011)3
  14. 14.
    Bernal-Marin, M., Bayro-Corrochano, E.: Integration of Hough transform of lines and planes in the framework of conformal geometric algebra for 2D and 3D robot vision. Pattern Recognit. Lett. 32(16), 2213–2223 (2011). doi: 10.1016/10.1016/j.patrec.2011.05.014 CrossRefGoogle Scholar
  15. 15.
    Grant, W., Voorhies, R., Itti, L.: Finding planes in LiDAR point clouds for real-time registration. In: Proceedings of the 2013 IEEE/RSJ International Conference Intelligent Robots and Systems IROS, pp. 4347–4354 (Nov 2013). doi: 10.1109/IROS.2013.6696980
  16. 16.
    Hulik, R., et al.: Continuous plane detection in point-cloud data based on 3D Hough Transform. J. Vis. Commun. Image Represent. 25(1), 86–97 (2014). doi: 10.1016/j.jvcir.2013.04.001 CrossRefGoogle Scholar
  17. 17.
    Limberger, F.A., Oliveira, M.M.: Real-time detection of planar regions in unorganized point clouds. Pattern Recognit. 48(6), 2043–2053 (2015). doi: 10.1016/j.patcog.2014.12.020 CrossRefGoogle Scholar
  18. 18.
    Chmielewski, L., Orłowski, A.: Ground level recovery from terrestrial laser scanning data with the variably randomized iterated hierarchical hough transform. In: Azzopardi, G., Petnov, N., (ed.) Proceedings of the International Conference on Computer Analysis of Images and Patterns CAIP 2015, vol. 9256 of LNCS., Valletta, Malta, Springer Verlag (2–4 Sep 2015) pp. 630–641 (Part I). doi: 10.1007/978-3-319-23192-1_53
  19. 19.
    Nieniewski, M., Chmielewski, L., Jóźwik, A., Skłodowski, M.: Morphological detection and feature-based classification of cracked regions in ferrites. Mach. Gr. Vis. 8(4), 699–712 (1999)Google Scholar
  20. 20.
    Jóźwik, A., Chmielewski, L., Skłodowski, M., Cudny, W.: A parallel net of (1-NN, k-NN) classifiers for optical inspection of surface defects in ferrites. Mach. Gr. Vis. 7(1–2), 99–112 (1998)Google Scholar
  21. 21.
    Mari, M., et al.: The CRASH Project: Defect detection and classification in ferrite cores. In: Bimbo, A.D., (ed.) Proceedings of the 9th International Conference on Image Analysis and Processing, vol. 1310 of LNCS., Florence, Italy, Springer Verlag (17–19 Sep 1997) pp. 781–787 (vol. II)Google Scholar
  22. 22.
    SMARTTECH Ltd.: Scanner scan3D dual volume (2015). http://smarttech3dscanner.com/3d-scanners/for-industry/scan3d-dual-volume/. Accessed 09 Mar 2015
  23. 23.
    Habib, A., Schenk, T.: New approach for matching surfaces from laser scanners and optical sensors. In: Csatho, B.M., (ed.): Proceedings of the Joint Workshop of ISPRS III/5 and III/2 on Mapping Surface Structure and Topography by Air-borne and Space-borne Lasers, La Jolla, San Diego, CA (9–11 Nov 1999)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Leszek J Chmielewski
    • 1
  • Katarzyna Laszewicz-Śmietańska
    • 2
  • Piotr Mitas
    • 2
  • Arkadiusz Orłowski
    • 1
  • Jarosław Górski
    • 2
  • Grzegorz Gawdzik
    • 1
  • Maciej Janowicz
    • 1
  • Jacek Wilkowski
    • 2
  • Piotr Podziewski
    • 2
  1. 1.Faculty of Applied Informatics and Mathematics (WZIM)Warsaw University of Life Sciences (SGGW)WarsawPoland
  2. 2.Faculty of Wood Technology (WTD)Warsaw University of Life Sciences (SGGW)WarsawPoland

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