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Computing Entropy Maps of Finite-Automaton-Encoded Binary Images

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Automata Implementation (WIA 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2214))

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Abstract

Finite automata are being used to encode images. Applications of this technique include image compression, and extraction of self similarity information and Hausdorff dimension of the encoded image. Jürgensen and Staiger [7] proposed a method by which the local Hausdorff dimension of the encoded image could be effectively computed. This paper describes the first implementation of this procedure and presents some experimental results showing local entropy maps computed from images represented by finite automata.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Western Ontario, London, Ontario, N6A 5B7, Canada

    Mark G. Eramian

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  1. Mark G. Eramian
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Editor information

Editors and Affiliations

  1. Universität Potsdam, Institut für Informatik, August-Bebel-Straße 89, 14482, Potsdam, Germany

    Oliver Boldt

  2. Institut für Informatik, Universität Potsdam, Potsdam

    Helmut Jürgensen

  3. Department of Computer Science, The University of Western Ontario, London, Ontario, Canada, N6A 5B7

    Helmut Jürgensen

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© 2001 Springer-Verlag Berlin Heidelberg

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Eramian, M.G. (2001). Computing Entropy Maps of Finite-Automaton-Encoded Binary Images. In: Boldt, O., Jürgensen, H. (eds) Automata Implementation. WIA 1999. Lecture Notes in Computer Science, vol 2214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45526-4_8

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  • DOI: https://doi.org/10.1007/3-540-45526-4_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42812-1

  • Online ISBN: 978-3-540-45526-4

  • eBook Packages: Springer Book Archive

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