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Iris Recognition Using LVQ Neural Network

  • Seongwon Cho
  • Jaemin Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

In this paper, we discuss human iris recognition, which is based on iris localization, feature extraction, and classification. The features for iris recognition are extracted from the segmented iris pattern using two-dimensional (2-D) wavelet transform based on Haar wavelet. We present an efficient initialization method of the weight vectors and a new method to determine the winner in LVQ neural network. The proposed methods have more accuracy than the conventional techniques.

Keywords

Weight Vector Input Vector Classification Performance Iris Image Haar Wavelet 
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 2006

Authors and Affiliations

  • Seongwon Cho
    • 1
  • Jaemin Kim
    • 1
  1. 1.School of Electronic and Electrical EngineeringHongik UniversitySeoulKorea

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