Face recognition using modular neural networks and the fuzzy Sugeno integral for response integration: Research Articles

Authors:
Patricia Melin;Cristina Felix;Oscar Castillo
Affiliations:
Department of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico;Department of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico;Department of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico
Venue:
International Journal of Intelligent Systems - Soft Computing for Modeling, Simulation, and Control of Nonlinear Dynamical Systems
Year:
2005

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Abstract

We describe a new approach for face recognition using modular neural networks with a fuzzy logic method for response integration. We proposed a new architecture for modular neural networks for achieving pattern recognition in the particular case of human faces. Also, the method for achieving response integration is based on the fuzzy Sugeno integral. Response integration is required to combine the outputs of all the modules in the modular network. We have applied the new approach for face recognition to a real database of faces of students at our institution. Recognition rates with the modular approach were compared against the monolithic single neural network approach to measure the improvement. The results of the new modular neural network approach were excellent overall and also in comparison to the monolithic approach. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 275–291, 2005.