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High Order Cellular Automata for Edge Detection: A Preliminary Study

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Cellular Automata (ACRI 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12599))

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Abstract

In this paper we explore the possibility of using high-order cellular automata to perform edge detection. Experiments are conducted to show how to find optimal values for the model. Using these optimal values, the model is compared to common methods for edge detection. The obtained results are encouraging since they are very close to the best performing commonly used methods.

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Author information

Authors and Affiliations

  1. Université Côte d’Azur, CNRS, I3S, Nice, France

    Enrico Formenti

  2. Université Côte d’Azur, Villa Arson, Nice, France

    Jean-Louis Paquelin

Authors
  1. Enrico Formenti
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  2. Jean-Louis Paquelin
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Corresponding author

Correspondence to Enrico Formenti .

Editor information

Editors and Affiliations

  1. University of Łódź, Lodz, Poland

    Tomasz M. Gwizdałła

  2. Università degli Studi di Trieste, Trieste, Italy

    Luca Manzoni

  3. Democritus University of Thrace, Xanthi, Greece

    Georgios Ch. Sirakoulis

  4. University of Milano-Bicocca, Milan, Italy

    Stefania Bandini

  5. University of Łódź, Lodz, Poland

    Krzysztof Podlaski

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Formenti, E., Paquelin, JL. (2021). High Order Cellular Automata for Edge Detection: A Preliminary Study. In: Gwizdałła, T.M., Manzoni, L., Sirakoulis, G.C., Bandini, S., Podlaski, K. (eds) Cellular Automata. ACRI 2020. Lecture Notes in Computer Science(), vol 12599. Springer, Cham. https://doi.org/10.1007/978-3-030-69480-7_9

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  • DOI: https://doi.org/10.1007/978-3-030-69480-7_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-69479-1

  • Online ISBN: 978-3-030-69480-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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