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Image compression using Weighted Finite Automata

  • Karel CulikII
  • Jarkko Kari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 711)

Abstract

We introduce Weighted Finite Automata (WFA) as a tool to define real functions, in particular, the greyness functions of grey-tone images. Mathematical properties and the definition power of WFA have been studied by Culik and Karhumäki. Their generative power is incomparable with Barnsley's Iterative Function Systems. Here, we give an automatic encoding algorithm that converts an arbitrary grey-tone-image (a digitized photograph) into a WFA that can regenerate it (with or without information loss). The WFA seems to be the first image definition tool with such a relatively simple encoding algorithm.

Keywords

Image Compression Encode Algorithm Finite Automaton Greyness Function Average Preserve 
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 1993

Authors and Affiliations

  • Karel CulikII
    • 1
  • Jarkko Kari
    • 2
  1. 1.Department of Computer ScienceUniversity of South CarolinaColumbiaUSA
  2. 2.Department of MathematicsUniversity of TurkuTurkuFinland

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