Genetic Optimization of Neural Networks for Person Recognition Based on the Iris
Abstract: This paper describes
the application of modular neural network architectures for person recognition
using the human iris image as a biometric measure. The iris database was
obtained from the Institute of Automation of the Academy of Sciences China
(CASIA). We show simulation results with the modular neural network approach,
its optimization using genetic algorithms, and the integration with different
methods, such as: the gating network method, type-1 fuzzy integration and
optimized fuzzy integration using genetic algorithms. Simulation results show a
good identification rate using fuzzy integrators and the best structure found
by the genetic algorithm.
Author: Patricia Melin, Victor
Herrera, Danniela Romero, Fevrier Valdez, Oscar Castillo
Journal Code: jptkomputergg120054
