Periocular Recognition Using Retinotopic Sampling and Gabor Decomposition

  • Fernando Alonso-Fernandez
  • Josef Bigun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7584)


We present a new system for biometric recognition using periocular images based on retinotopic sampling grids and Gabor analysis of the local power spectrum. A number of aspects are studied, including: 1) grid adaptation to dimensions of the target eye vs. grids of constant size, 2) comparison between circular- and rectangular-shaped grids, 3) use of Gabor magnitude vs. phase vectors for recognition, 4) rotation compensation between query and test images, and 5) comparison with an iris machine expert. Results show that our system achieves competitive verification rates compared with other periocular recognition approaches. We also show that top verification rates can be obtained without rotation compensation, thus allowing to remove this step for computational efficiency. Also, the performance is not affected substantially if we use a grid of fixed dimensions, or it is even better in certain situations, avoiding the need of accurate detection of the iris region.


Biometrics periocular eye iris Log-Polar mapping Gabor decomposition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Fernando Alonso-Fernandez
    • 1
  • Josef Bigun
    • 1
  1. 1.Halmstad UniversityHalmstadSweden

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