Modular Neural Networks for Person Recognition Using the Contour Segmentation of the Human Iris

  • Patricia Melin
Part of the Studies in Computational Intelligence book series (SCI, volume 389)

Abstract

This chapter presents three modular neural network architectures as systems for recognizing persons based on the iris biometric measurement of humans [80]. In these systems, the human iris database is enhanced with image processing methods, and the coordinates of the center and radius of the iris are obtained to make a cut of the area of interest by removing the noise around the iris. The inputs to the modular neural networks are the processed iris images and the output is the number of the person identified. The integration of the modules was done with a gating network method [59].

Keywords

Hide Layer Identification Rate Adaptive Learning Biometric Measurement Scaled Conjugate Gradient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Patricia Melin

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