A heuristic model for optimizing fuzzy knowledge base in a pattern recognition system

Abstract

341-347This study presents a genetic algorithm (GA) to optimize performance of a fuzzy system for reconition of facial expression from images. In proposed model, a Mamdani-type fuzzy rule based system recognizes emotions, and a GA is used to improve accuracy and robustness of the system. To evaluate system performance, images from FG-Net (FEED) and Cohn-Kanade database were used to obtain the best functions parameters. Proposed model under training process not only increased accuracy rate of emotion recognition but also increased validity of the model in adverse conditions