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Evolutionary Cellular Automata Based-Approach for Edge Detection

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Applications of Fuzzy Sets Theory (WILF 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4578))

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Abstract

We use an evolutionary process to seek a specialized powerful rule of Cellular Automata (CA) among a set of best rules for extracting edges in a given black-white image. This best set of local rules determines the future state of CA in an asynchronous way. The Genetic Algorithm (GA) is applied to search the best CA rules that can realize better the edge detection.

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Author information

Authors and Affiliations

  1. University of Biskra, Computer Science department, 07000 Biskra, Algeria

    Sihem Slatnia & Kamal E. Melkemi

  2. Computer Science department, College of Computer and Information Sciences, University of King Saud, Saudi Arabia

    Mohamed Batouche

Authors
  1. Sihem Slatnia
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  2. Mohamed Batouche
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  3. Kamal E. Melkemi
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Editor information

Francesco Masulli Sushmita Mitra Gabriella Pasi

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© 2007 Springer-Verlag Berlin Heidelberg

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Slatnia, S., Batouche, M., Melkemi, K.E. (2007). Evolutionary Cellular Automata Based-Approach for Edge Detection. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_51

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  • DOI: https://doi.org/10.1007/978-3-540-73400-0_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73399-7

  • Online ISBN: 978-3-540-73400-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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