Crack-Free Isosurface of Volumetric Scattered Data

  • Han Sol Shin
  • Jee Ho Song
  • Tae Jun Yu
  • Kun LeeEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10919)


Isosurface extraction is the method of visualizing multivariate data in three-dimensional space. It is an important process to observe geometrical distribution of iso-value by isosurface extraction. Data obtained by PIC (Particle In Cell) simulation have a characteristic of irregularly distributed volumetric scattered data. Unlike curved surfaces of implicit function, PIC simulation data cannot be represented by continuous function, and each points have no relationship. In such case, isosurface extraction algorithms do not guarantee crack-free surfaces on their results. This paper describes how we get smooth approximation of volumetric scattered data by using a natural neighbor interpolation, and extract a crack-free isosurface on interpolated data.


Isosurface Volumetric scattered data Data visualization 



This work was supported by the Industrial Strategic technology development program, 10048964, Development of 125 J\( \cdot \)Hz laser system for laser peering funded by Ministry of Trade, Industry & Energy (MI, republic of Korea).


  1. 1.
    Rübel, O., Geddes, C.G.R., Chen, M., Cormier-Michel, E., Bethel, E.W.: Feature-based analysis of plasma-based particle acceleration data. IEEE Trans. Vis. Comput. Graph. 20(2), 196–210 (2014)CrossRefGoogle Scholar
  2. 2.
    Wenger, R.: Isosurfaces, pp. 1–16. CRC Press, Boca Raton (2013)Google Scholar
  3. 3.
    Telea, A.C.: Data Visualization: Principles and Practice 2nd edn. CRC Press, Boca Raton (2015)Google Scholar
  4. 4.
    Nielson, G.M.: Scattered data modeling. IEEE Comput. Graph. Appl. 13, 60–70 (1993)CrossRefGoogle Scholar
  5. 5.
    Lorensen, W.E., Cline, H.E.: Marching cubes: a high resolution 3D surface construction algorithm. Comput. Graph. 21(4), 163–169 (1987)CrossRefGoogle Scholar
  6. 6.
    Dyken, C., Ziegler, G., Theobalt, C., Seidel, H.-P.: High-speed Marching Cubes using HistoPyramids. Comput. Graph. Forum 27(8), 2028–2039 (2008)CrossRefGoogle Scholar
  7. 7.
    Lee, K.: Visualization of trivariate scattered data interpolation. J. Korea Comput. Graph. Soc. 2(2), 11–20 (1996)Google Scholar
  8. 8.
    Sibson, R.: A brief description of natural neighbour interpolation. In: Barnett, V. (ed.) Interpreting Multivariate Data, pp. 21–36. Wiley, New York (1981)Google Scholar
  9. 9.
    Boissonnat, J.D., Cazals, F.: Smooth surface reconstruction via natural neighbour interpolation of distance functions. Comput. Geometry 22, 185–203 (2002)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Ledoux, H., Gold, C.: An efficient natural neighbour interpolation algorithm for geoscientific modelling. In: Developments in Spatial Data Handling, pp. 91–108. Springer, Heidelberg (2005).

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Han Sol Shin
    • 1
  • Jee Ho Song
    • 1
  • Tae Jun Yu
    • 2
  • Kun Lee
    • 3
    Email author
  1. 1.Department of Information and CommunicationHandong Global UniversityPohangRepublic of Korea
  2. 2.Department of Advanced Green Energy and EnvironmentHandong Global UniversityPohangRepublic of Korea
  3. 3.School of Computer Science and Electronic EngineeringHandong Global UniversityPohangRepublic of Korea

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