Open AccessOptimization of fuzzy image pattern matching using genetic algorithm
Author(s) -
D. Ravikumar,
Arun Raaza,
V. Uma devi
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.33.14827
Subject(s) - fuzzy logic , pattern recognition (psychology) , artificial intelligence , computer science , matching (statistics) , segmentation , template , fuzzy classification , fuzzy set , algorithm , mathematics , statistics , programming language
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.