Automatic selection of input variables and initialization parameters in an adaptive neuro fuzzy inference system: application for modeling visual textures in digital images

Authors:
A. Mejías;O. Sánchez;S. Romero
Affiliations:
Escuela Politécnica Superior, Huelva University, La Rábida, Huelva, Spain;Escuela Politécnica Superior, Huelva University, La Rábida, Huelva, Spain;Escuela Politécnica Superior, Huelva University, La Rábida, Huelva, Spain
Venue:
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Year:
2007

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Abstract

In this paper we present a method for the automatic selection of input variables and some previous parameters, such as number and type of membership functions, in an Adaptive Neuro Fuzzy Inference System (ANFIS) using a Genetic Algorithm with a new fitness function. Both of them constitute a design scheme that we will use for modeling the perception of textures in Digital Images. Some examples are presented, training ANFIS with this scheme for modeling the following visual textures: coarseness, directionality and regularity.