Abstract
This chapter describes the application of modular neural network architecture for the recognition of persons using the human iris images [80]; the iris database was obtained from the Institute of Automation of the Academy of Sciences China (CASIA). We show the results of testing the modular neural network, its optimization using genetic algorithms and the integration with the methods of gating network, type-1 fuzzy integration, and fuzzy integration optimized by genetic algorithms. Simulation results show a good identification using the fuzzy integrators and the best structure found by the genetic algorithm.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Melin, P. (2012). Neural Network Optimization for the Recognition of Persons Using the Iris Biometric Measure. In: Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition. Studies in Computational Intelligence, vol 389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24139-0_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-24139-0_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24138-3
Online ISBN: 978-3-642-24139-0
eBook Packages: EngineeringEngineering (R0)