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Admissible Perturbation of Demicontractive Operators within Ant Algorithms for Medical Images Edge Detection

Author

Listed:
  • Cristina Ticala

    (Technical University of Cluj-Napoca, North University Center of Baia Mare, 400114 Cluj-Napoca, Romania)

  • Ioana Zelina

    (Technical University of Cluj-Napoca, North University Center of Baia Mare, 400114 Cluj-Napoca, Romania)

  • Camelia-M. Pintea

    (Technical University of Cluj-Napoca, North University Center of Baia Mare, 400114 Cluj-Napoca, Romania)

Abstract

Nowadays, demicontractive operators in terms of admissible perturbation are used to solve difficult tasks. The current research uses several demicontractive operators in order to enhance the quality of the edge detection results when using ant-based algorithms. Two new operators are introduced, χ -operator and K H -operator, the latter one is a Krasnoselskij admissible perturbation of a demicontractive operator. In order to test the efficiency of the new operators, a comparison is made with a trigonometric operator. Ant Colony Optimization (ACO) is the solver chosen for the images edge detection problem. Demicontractive operators in terms of admissible perturbation are used during the construction phase of the matrix of ants artificial pheromone, namely the edge information of an image. The conclusions of statistical analysis on the results shows a positive influence of proposed operators for image edge detection of medical images.

Suggested Citation

  • Cristina Ticala & Ioana Zelina & Camelia-M. Pintea, 2020. "Admissible Perturbation of Demicontractive Operators within Ant Algorithms for Medical Images Edge Detection," Mathematics, MDPI, vol. 8(6), pages 1-13, June.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:6:p:1040-:d:376563
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    References listed on IDEAS

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    1. Lahrichi, Nadia & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter & Crişan, Gloria Cerasela & Vidal, Thibaut, 2015. "An integrative cooperative search framework for multi-decision-attribute combinatorial optimization: Application to the MDPVRP," European Journal of Operational Research, Elsevier, vol. 246(2), pages 400-412.
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    Cited by:

    1. Li-Jun Zhu & Yonghong Yao, 2023. "Algorithms for Approximating Solutions of Split Variational Inclusion and Fixed-Point Problems," Mathematics, MDPI, vol. 11(3), pages 1-12, January.

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