Neural Networks Using Hausdorff Distance, SURF and Fisher Algorithms for Ear Recognition

  • Pedro Luis Galdámez
  • María Angélica González Arrieta
  • Miguel Ramón Ramón
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 299)

Abstract

The purpose of this paper is to offer an approach in the biometrics analysis field, using ears to recognize people. This study uses Hausdorff distance as a preprocessing stage adding sturdiness to increase the performance filtering for the subjects to use for testing stage of the neural network. Then, the system computes Speeded Up Robust Features (SURF) and Fisher Linear Discriminant Analysis (LDA) as an input of two neural networks to detect and recognize a person by the patterns of its ear. To show the applied theory in the experimental results; it also includes an application developed with Microsoft .net. The investigation which enhances the ear recognition process showed robustness through the integration of Hausdorff, LDA and SURF in neural networks.

Keywords

Neural Network Hausdorff LDA SURF Ear Recognition 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Pedro Luis Galdámez
    • 1
  • María Angélica González Arrieta
    • 1
  • Miguel Ramón Ramón
    • 1
  1. 1.University of SalamancaSalamancaSpain

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