Face Recognition with Modular Neural Networks and Fuzzy Measures

Abstract

We describe in this chapter a new approach for face recognition using modular neural networks with a fuzzy logic method for response integration. We describe 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 with a real database of faces from students and professors of 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 gives excellent performance overall and also in comparison with the monolithic approach. The chapter is divided as follows: first we give a brief introduction to the problem of face recognition, second we describe the proposed architecture for achieving face recognition, third, we describe the fuzzy method for response integration, and finally we show a summary of the results and conclusions.