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Cellular Automata Enhanced Quantum Inspired Edge Detection

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Fuzzy Logic in Intelligent System Design (NAFIPS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 648))

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Abstract

The developing of techniques for image processing based on quantum-inspired algorithms is a recent subject of study with promising results. Quantum-inspired edge detecting algorithms are a novel approach to detect fine details, especially in medical images. Since quantum inspired algorithms based on quantum measurement are susceptible to some noise related to their probabilistic nature their output can be degraded. This work proposes a quantum-inspired edge detection algorithm with an enhancement stage using cellular automata to reduce the degradation of the detected edges. The proposed method uses gradient operators applied to grayscale images that will be the input for a quantum-inspired measurement stage. After the measurement, a cellular automaton is used to eliminate noise and to obtain thinner edges. Comparative results are presented.

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Acknowledgements

We thank Instituto Politécnico Nacional (IPN), to the Comisión de Fomento y Apoyo Académico del IPN (COFAA), and to the Mexican National Council of Science and Technology (CONACYT) for supporting our research activities.

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Authors and Affiliations

  1. Centro de Investigación y Desarrollo de Tecnología Digital (CITEDI-IPN), Instituto Politécnico Nacional, Av. Instituto Politécnico Nacional No. 1310, Colonia Nueva Tijuana, 22435, Tijuana, BC, Mexico

    Yoshio Rubio, Oscar Montiel & Roberto Sepúlveda

Authors
  1. Yoshio Rubio
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  2. Oscar Montiel
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  3. Roberto Sepúlveda
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Corresponding author

Correspondence to Oscar Montiel .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Reformat

  5. Laboratory of Computational Intelligence and Automation, University of Waterloo, Waterloo, Ontario, Canada

    William Melek

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Rubio, Y., Montiel, O., Sepúlveda, R. (2018). Cellular Automata Enhanced Quantum Inspired Edge Detection. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-67137-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67136-9

  • Online ISBN: 978-3-319-67137-6

  • eBook Packages: EngineeringEngineering (R0)

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