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Computing Entropy Maps of Finite-Automaton-Encoded Binary Images

  • Mark G. Eramian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2214)

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.

Keywords

Adjacency Matrix Binary Image Hausdorff Dimension Finite Automaton State Entropy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Mark G. Eramian
    • 1
  1. 1.Department of Computer ScienceUniversity of Western OntarioLondonCanada

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