Skip to main content

Medial Set, Boundary, and Topology of Random Point Sets

  • Conference paper
  • First Online:
  • 331 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2616))

Abstract

In this paper, we aim to develop an algorithm for the extraction of a medial set of a random point set in two-an d three-dimensional spaces. Using the medial set of a random point, we define the topology of a random point set. The algorithm for the extraction of a median set is based on the principal surface analysis.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Hasite, T., Stuetzle, T., Principal curves, J. Am. Statistical Assoc., 84, 502–516, 1989.

    Article  Google Scholar 

  2. Kégl, B., Krzyzak, A., Linder, T., Zeger, K., Learning and design of principal curves, IEEE PAMI, 22, 281–297, 2000.

    Google Scholar 

  3. Oja, E., Principal components, minor components, and linear neural networks, Neural Networks, 5, 927–935, 1992.

    Article  Google Scholar 

  4. Imiya, A., Ootani, H., PCA-based model selection and fitting for linear manifolds, LNAI, 2123, 278–292, 2001.

    Google Scholar 

  5. Imiya, A., Kawamoto, K., Learning dimensionality and orientations of 3D objects, Pattern Recognition Letters, 22, 75–83, 2001.

    MATH  Google Scholar 

  6. Blum, H., Biological shape and visual science, J. Theoretical Biology, 38, 205–285, 1963.

    Article  Google Scholar 

  7. Rosenfeld, A., Axial representations of shapes, CVGIP, 33, 156–173, 1986.

    Google Scholar 

  8. Bookstein, F. L., The line-skeleton, CVGIP, 11, 1233–137, 1979

    Google Scholar 

  9. Amenta, N., Bern, M., Eppstein, D., The crust and the â-skeleton: Combinatorial curve reconstruction, Graphical Models and Image Processing, 60, 125–135, 1998.

    Google Scholar 

  10. Attali, D. and Montanvert, A., Computing and simplifying 2D and 3D continuous skeletons, CVIU, 67, 261–273, 1997.

    Google Scholar 

  11. Nystrom, I., Sanniti di Baja, G., Svensson, S., Curve skeletonization by junction detection Lecture Notes in Computer Science 2059, 229–238, 2001.

    Google Scholar 

  12. Svensson, S., Nystrom, I., Sanniti di Baja, G., Curve skeletonization of surfacelike objects in 3D images guided by voxel classification, Pattern Recognition Letters, 23, 1419–1426, 2002.

    MATH  Google Scholar 

  13. Sanniti di Baja, G., Svensson, S., Surface skeletons detected on the D6 distance transform. Lecture Notes in Computer Science 1876, 387–396, 2000.

    Google Scholar 

  14. Svensson, S., Borgefors, G., Nystrom, I., On reversible skeletonization using anchor-points from distance transforms Journal on Visual Communication and Image Representation 10, 379–397, 1999.

    Article  Google Scholar 

  15. Svensson, S., Sanniti di Baja, G., Using distance transforms to decompose 3D discrete objects, Image and Vision Computing, 20, 529–540, 2002.

    Article  Google Scholar 

  16. Silverman, B.W., Some aspects of the spline smoothing approach to nonparametric regression curve fitting, J.R. Statist. Soc, B. 47, 1–52, 1985.

    MATH  Google Scholar 

  17. Wahba, G., Surface fitting with scattered noisy data on Euclidean D-space and on the sphere, Rocky Mountain Journal of Mathematics, 14, 281–299, 1984.

    Article  MATH  MathSciNet  Google Scholar 

  18. Reed, M.K., Allen, A.K., 3-D modeling from range imagery, Image and Vision Computing, 17, 99–111, 1999.

    Article  Google Scholar 

  19. Terzopoulos, D., The computation of visible-surface representations, IEEE PAMI, 10, 417–438, 1988.

    MATH  Google Scholar 

  20. Freedman, D., Efficient simplicial reconstruction of manifolds from their samples, IEEE PAMI, 24, 1349–1357, 2002.

    Google Scholar 

  21. Li, W. and Swetits, J. J., The linear l2 estimation and the Huber M-estimator, SIAM J. Optimization 8, 457–475, 1998.

    Article  MATH  MathSciNet  Google Scholar 

  22. Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., Stuetzle, W., Surface reconstruction from unorganized points, “Computer Graphics (SIGGRAPH’ 92 Proceedings)”, 26, 71–78, 1992.

    Google Scholar 

  23. Taubin, G. Detecting and reconstructing subdivision connectivity, The Visual Computer, Vol18, 357–367, 2002.

    Google Scholar 

  24. Taubin, G., Ronfard, R., Implicit simplical models I: Adaptive curve reconstruction, PAMI, 18, 321–325, 1996.

    Google Scholar 

  25. Edelsbrunner, H., Shape reconstruction with Delaunay complex, Lecture Notes in Computer Science, 1380, 119–132, 1998.

    Google Scholar 

  26. Martinetz, T., and Schulten, K., Topology representing networks, Neural Networks, 7, 507–522, 1994.

    Article  Google Scholar 

  27. Huisken, G., Flow by mean curvature of convex surface into sphere, Journal of Differential Geometry, 20, 237–266, 1984.

    MATH  MathSciNet  Google Scholar 

  28. Bruckstein, A.M., Shapiro, G., and Shaked, D., Evolution of planar polygons, Journal of Pattern Recognition and Artificial Intelligence, 9, 991–1014, 1995.

    Article  Google Scholar 

  29. Zhao, H.-K., Osher, S., Merriman, B., and Kang, M., Implicit and nonparametric shape reconstruction from unorganized points using variational level set method, CVIU, 80, 285–319, 2000.

    Google Scholar 

  30. Sethian, J. A., Level Set Methods: Evolving Interfaces in Geometry Fluid Mechanics, Computer Vision, and Material Science. Cambridge University Press, Cambridge, 1996.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Imiya, A., Ootani, H., Tatara, K. (2003). Medial Set, Boundary, and Topology of Random Point Sets. In: Asano, T., Klette, R., Ronse, C. (eds) Geometry, Morphology, and Computational Imaging. Lecture Notes in Computer Science, vol 2616. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36586-9_13

Download citation

  • DOI: https://doi.org/10.1007/3-540-36586-9_13

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00916-0

  • Online ISBN: 978-3-540-36586-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics