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A new algorithm for probabilistic relaxation based on the Baum Eagon theorem

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Computer Analysis of Images and Patterns (CAIP 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 970))

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Abstract

The update equations for Kittler Hancock probabilistic relaxation are solved exactly for a model problem. The solution reveals deficiencies of the support function. We formulate a new form of probabilistic relaxation heuristically based on the Baum Eagon theorem. The new algorithm gives the MAP labelling for the model problem.

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References

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, University of Surrey, GU2 5XH, Guildford, UK

    A. J. Stoddart, M. Petrou & J. Kittler

Authors
  1. A. J. Stoddart
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  2. M. Petrou
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  3. J. Kittler
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Editor information

Václav Hlaváč Radim Šára

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© 1995 Springer-Verlag Berlin Heidelberg

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Stoddart, A.J., Petrou, M., Kittler, J. (1995). A new algorithm for probabilistic relaxation based on the Baum Eagon theorem. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_363

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  • DOI: https://doi.org/10.1007/3-540-60268-2_363

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60268-2

  • Online ISBN: 978-3-540-44781-8

  • eBook Packages: Springer Book Archive

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