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Skeletonizing Digital Images with Cellular Automata

  • Chapter
Cellular Automata in Image Processing and Geometry

Part of the book series: Emergence, Complexity and Computation ((ECC,volume 10))

Abstract

The skeletonization of an image consists of converting the initial image into a more compact representation. In general, the skeleton preserves the basic structure and, in some sense, keeps the meaning. The most important features concerning a shape are its topology (represented by connected components, holes, etc.) and its geometry (elongated parts, ramifications, etc.), thus they must be preserved. Skeletonization is usually considered as a pre-processing step in pattern recognition algorithms, but its study is also interesting by itself for the analysis of line-based images such as texts, line drawings, human fingerprints classification or cartography.

Since the introduction of the concept by Blum in 1962 under the name of medial axis transform, many algorithms have been published in this topic and there are many different approaches to the problem, among them the ones based on distance transform of the shape and skeleton pruning based on branch analysis. In this chapter, we focus on how the skeletonization of an image can be studied in the Cellular Automata framework and, as a case study, we consider in detail the Guo and Hall skeletonizing algorithm.

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Author information

Authors and Affiliations

  1. Research Group on Computational Topology and Applied Mathematics, Department of Applied Mathematics, University of Seville, Seville, Spain

    Daniel Díaz-Pernil

  2. Research Group on Natural Computing, Department of Computer Science and Artificial Intelligence, University of Seville, Seville, Spain

    Francisco Peña-Cantillana & Miguel A. Gutiérrez-Naranjo

Authors
  1. Daniel Díaz-Pernil
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  2. Francisco Peña-Cantillana
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  3. Miguel A. Gutiérrez-Naranjo
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Corresponding author

Correspondence to Daniel Díaz-Pernil .

Editor information

Editors and Affiliations

  1. School of Computer Science & Informatics, Cardiff University, Cardiff, United Kingdom

    Paul Rosin

  2. Unconventional Computing Centre, University of the West of England, Bristol, United Kingdom

    Andrew Adamatzky

  3. School of Computer Science & Informatics, Cardiff University, Cardiff, United Kingdom

    Xianfang Sun

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Díaz-Pernil, D., Peña-Cantillana, F., Gutiérrez-Naranjo, M.A. (2014). Skeletonizing Digital Images with Cellular Automata. In: Rosin, P., Adamatzky, A., Sun, X. (eds) Cellular Automata in Image Processing and Geometry. Emergence, Complexity and Computation, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-06431-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-06431-4_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06430-7

  • Online ISBN: 978-3-319-06431-4

  • eBook Packages: EngineeringEngineering (R0)

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