Skip to main content

Part of the book series: Computational Imaging and Vision ((CIVI,volume 2))

Abstract

A tessellation which is capable of producing rough boundaries is proposed. Some properties of the proposed tessellation are also described.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adams, R. and Bischof, L.: 1994,’Seeded Region Growing’, IEEE Transactions on Pattern Analysis and Machine Intelligence, (in press).

    Book  Google Scholar 

  2. Barnsley, M.: 1988, Fractals Everywhere, Academic Press.

    MATH  Google Scholar 

  3. Batchelor, M. T. and Henry, B. I.: 1991,’Limits to Eden growth in two and three dimensions’,Physics Letters A, 157, 229–236.

    Article  Google Scholar 

  4. Bramson, M. and Griffeath, D.: 1981,’On the Williams-Bjerknes tumour growth model I’, The Annals of Probability, 9, 173–185.

    Article  MathSciNet  MATH  Google Scholar 

  5. Cressie, N. A. C.: 1991, Statistics for Spatial Data, Wiley-Interscience.

    MATH  Google Scholar 

  6. Durrett, R. and Liggett, T. M.: 1981,’The shape of the limit set in Richardson’s growth model’, The Annals of Probability, 9, 186–193.

    Article  MathSciNet  MATH  Google Scholar 

  7. Eden, M.: 1961,’A two dimensional growth process’, Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, IV, J. Neyman, ed. University of California Press, Berkeley, CA, 223–239.

    Google Scholar 

  8. Richardson, D.: 1973,’Random growth in a tessellation’, Mathematical Proceedings of the Cambridge Philosophical Society, 74, 515–528.

    Article  MATH  Google Scholar 

  9. Stoyan, D., Kendall, W.S. and Mecke, J.: 1987, Stochastic Geometry and its Applications, Wiley: Chichester.

    MATH  Google Scholar 

  10. Szép, J., Cserti, J. and Kertész, J.: 1985,’Monte Carlo approach to dendritic growth’, Journal of Physics A, 18, L413–L418.

    Article  Google Scholar 

  11. Williams, T. and Bjerknes, R.: 1972,’Stochastic model for abnormal clone spread through epithelial basal layer’, Nature, 236,19–21.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1994 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Lee, T.C.M., Cowan, R. (1994). A Stochastic Tessellation of Digital Space. In: Serra, J., Soille, P. (eds) Mathematical Morphology and Its Applications to Image Processing. Computational Imaging and Vision, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1040-2_28

Download citation

  • DOI: https://doi.org/10.1007/978-94-011-1040-2_28

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-4453-0

  • Online ISBN: 978-94-011-1040-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics