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Separated Medial Surface Extraction from CT Data of Machine Parts

  • Tomoyuki Fujimori
  • Yohei Kobayashi
  • Hiromasa Suzuki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4077)

Abstract

This paper describes a new method for extracting separated medial surfaces from CT (Computed Tomography) data of machine parts. Plate structures are common mechanical structures such as car body shells. When designing such structures in CAD (Computer Aided Design) and CAE (Computer Aided Engineering) systems, their shapes are usually represented as surface models associated with their thickness values. In this research we are aiming at extracting medial surface models of a plate structure from its CT data so as to be used in CAD and CAE systems. However, such a structure consist of many components which are adjacent each other. For example, car body shells are consist of many welded plates. CT imaging technology has some weak points in the area. One of them is that, if there are two or more objects made of same material, CT scanner cannot make the distinction between them. The problem is caused by the principles of CT imaging technology. Because CT image represents the mass distribution within a cross section, we cannot separate the objects only from image information. However, there are many requests for scanning assembled parts and separating objects made of same material. Therefore, we propose a method to separate each components. CT data has not enough information amount as has been metinoned, so we adopt other knowledge about model shapes. We conclude with experiments on welded mechine parts for effectiveness of our method.

Keywords

Medial Cell Combine Region Geodesic Distance Machine Part Medial Surface 
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.

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References

  1. 1.
    Sheehy, D.J., Armstrong, C.G., Robinson, D.J.: Computing the medial surface of a solid from a domain delaunay triangulation. In: Proceedings of the third ACM symposium on Solid modeling and applications, pp. 201–212. ACM Press, New York (1995)CrossRefGoogle Scholar
  2. 2.
    Fujimori, T., Suzuki, H., Kobayashi, Y., Kase, K.: Contouring medial surface of thin plate structure using local marching cubes. Journal of Computing and Information Science in Engineering (Short Paper) 5(2), 111–115 (2005)CrossRefGoogle Scholar
  3. 3.
    Lorensen, W.E., Cline, H.E.: Marching cubes: A high resolution 3d surface construction algorithm. In: Proceedings of the 14th annual conference on Computer graphics and interactive techniques, pp. 163–169. ACM Press, New York (1987)CrossRefGoogle Scholar
  4. 4.
    Lam, L., Lee, S.W., Suen, C.Y.: Thinning methodologies–a comprehensive survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(9), 869–885 (1992)CrossRefGoogle Scholar
  5. 5.
    Pudney, C.: Distance-ordered homotopic thinning: a skeletonization algorithm for 3d digital images. Comput. Vis. Image Underst. 72(3), 404–413 (1998)CrossRefGoogle Scholar
  6. 6.
    Gagvani, N., Silver, D.: Parameter-controlled volume thinning. CVGIP: Graph. Models Image Process. 61(3), 149–164 (1999)CrossRefGoogle Scholar
  7. 7.
    Malandain, G., Fernandez-Vidal, S.: Euclidean skeletons. IVC 16, 317–327 (1998)Google Scholar
  8. 8.
    Prohaska, S., Hege, H.C.: Fast visualization of plane-like structures in voxel data. In: Proceedings of the conference on Visualization 2002. IEEE Computer Society, Los Alamitos (2002)Google Scholar
  9. 9.
    Lorensen, W.E., Cline, H.E.: Marching cubes: A high resolution 3d surface construction algorithm. In: Proceedings of the 14th annual conference on Computer graphics and interactive techniques, pp. 163–169. ACM Press, New York (1987)CrossRefGoogle Scholar
  10. 10.
    Hege, H.C., Seebaß, M., Stalling, D., Zöckler, M.: A generalized marching cubes algorithm based on non-binary classifications. Technical Report SC-97-05, Zuse Institute Berlin (1997)Google Scholar
  11. 11.
    Gibson, S.F.F.: Using distance maps for accurate surface representation in sampled volumes. In: Proceedings of the 1998 IEEE symposium on Volume visualization, pp. 23–30. ACM Press, New York (1998)CrossRefGoogle Scholar
  12. 12.
    Kobbelt, L.P., Botsch, M., Schwanecke, U., Seidel, H.P.: Feature sensitive surface extraction from volume data. In: Proceedings of the 28th annual conference on Computer graphics and interactive techniques, pp. 57–66. ACM Press, New York (2001)CrossRefGoogle Scholar
  13. 13.
    Ju, T., Losasso, F., Schaefer, S., Warren, J.: Dual contouring of hermite data. In: Proceedings of the 29th annual conference on Computer graphics and interactive techniques, pp. 339–346. ACM Press, New York (2002)CrossRefGoogle Scholar
  14. 14.
    Hormann, K., Labsik, U., Meister, M., Greiner, G.: Hierarchical extraction of iso-surfaces with semi-regular meshes. In: Proceedings of the seventh ACM symposium on Solid modeling and applications, pp. 53–58. ACM Press, New York (2002)CrossRefGoogle Scholar
  15. 15.
    Esteve, J., Brunet, P., Vinacua, A.: Approximation of a variable density cloud of points by shrinking a discrete membrane. Technical Report LSI-02-75-R, Universitat Politècnica de Catalunya (2002)Google Scholar
  16. 16.
    Itoh, T., Yamaguchi, Y., Koyamada, K.: Volume thinning for automatic isosurface propagation. In: Proceedings of the 7th conference on Visualization 1996, pp. 303–310. IEEE Computer Society Press, Los Alamitos (1996)CrossRefGoogle Scholar
  17. 17.
    Lachaud, J.O., Montanvert, A.: Continuous analogs of digital boundaries: A topological approach to iso-surfaces. Graphical Models and Image Processing 62, 129–164 (2000)Google Scholar
  18. 18.
    Lohmann, G. (ed.): Volumetric Image Analysis. John Wiley & Sons, Ltd., Chichester (1998)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tomoyuki Fujimori
    • 1
  • Yohei Kobayashi
    • 2
  • Hiromasa Suzuki
    • 1
  1. 1.Research Center for Advanced Science and TechnologyThe University of Tokyo 
  2. 2.CREED Coorpolation 

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