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Image compression using Weighted Finite Automata

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Mathematical Foundations of Computer Science 1993 (MFCS 1993)

Part of the book series: Lecture Notes in Computer Science ((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.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of South Carolina, 29208, Columbia, S.C., USA

    Karel Culik II

  2. Department of Mathematics, University of Turku, 20500, Turku, Finland

    Jarkko Kari

Authors
  1. Karel Culik II
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  2. Jarkko Kari
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Andrzej M. Borzyszkowski Stefan Sokołowski

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© 1993 Springer-Verlag Berlin Heidelberg

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Culik, K., Kari, J. (1993). Image compression using Weighted Finite Automata. In: Borzyszkowski, A.M., Sokołowski, S. (eds) Mathematical Foundations of Computer Science 1993. MFCS 1993. Lecture Notes in Computer Science, vol 711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57182-5_31

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  • DOI: https://doi.org/10.1007/3-540-57182-5_31

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57182-7

  • Online ISBN: 978-3-540-47927-7

  • eBook Packages: Springer Book Archive

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