Optimization of fuzzy image pattern matching using genetic algorithm

  • Authors

    • Ravikumar D
    • Dr Arun Raaza
    • Dr V. Devi
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.14827
  • Fuzzy logic, Genetic Algorithm, Image Pattern Matching, Image Segmentation, Object Recognition and Localization, Templates.

  • Abstract

    The process of fuzzy image pattern recognizes object found in images by using the methods of fuzzy logic. Localization of object is al-so done. Fuzzy segmentation templates and operators, which fetch a large number of alternatives, constitute methods used in the method of fuzzy logic. Imperfect and imprecision of the input images and the templates images are in the consideration of fuzzy pattern matching and later incorporated in the matching process. This paper contemplates two methods one for fuzzy pattern and the other for the optimizing the matching scheme with a genetic algorithm. The process of optimization has its objective, in finding the location of reliable feature from a set of calibrated images through a simultaneous optimization of the templates and the segmentation function. Optimization has demonstrated and resulting a superior abstraction of the matches for an unobserved sample images and a good performance to the common method of pattern matching.

     

     


     

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  • How to Cite

    D, R., Arun Raaza, D., & V. Devi, D. (2018). Optimization of fuzzy image pattern matching using genetic algorithm. International Journal of Engineering & Technology, 7(2.33), 526-531. https://doi.org/10.14419/ijet.v7i2.33.14827

    Received date: 2018-06-30

    Accepted date: 2018-06-30

    Published date: 2018-06-08