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Feature Band Selection for Multispectral Iris Recognition

  • David Zhang
  • Zhenhua Guo
  • Yazhuo Gong
Chapter

Abstract

This work uses East Asian irides as research subjects and explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for black-based iris multispectral fusion, and find these bands, which will provide an important standard for selecting bands of spectral wavelengths for iris multispectral fusion, especially for the black iris recognition of East Asians. A multispectral acquisition system is first designed for imaging the iris at narrow spectral bands in the range of 420–940 nm. Next, a set of 60 human black iris images which correspond to the right and left eyes of 30 different subjects are acquired for an analysis. Finally, we have determined that 3 clusters are enough to represent the 10 feature bands of spectral wavelengths from 545 to 940 nm, using the agglomerative clustering based on an improved multigroup two-dimensional principal component analysis [(2D)2PCA]. The experimental results suggest: (a) the number, center, and composition of clusters of spectral wavelengths and (b) the interference and potential impact of interference on the performance of iris multispectral fusion.

Keywords

Mutlispectral iris (2D)2PCA Feature band Clustering 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Biometrics Research CentreThe Hong Kong Polytechnic UniversityHung HomHong Kong SAR
  2. 2.Shenzhen Key Laboratory of Broadband Network & Multimedia, Graduate School at ShenzhenTsinghua UniversityShenzhenChina
  3. 3.University of Shanghai for Science and TechnologyShanghaiChina

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