Noisy Iris Recognition Integrated Scheme

  • Authors:
  • Maria De Marsico;Michele Nappi;Daniel Riccio

  • Affiliations:
  • Sapienza Universití di Roma, Via Salaria 13, 00198 Roma, Italy;Universití di Salerno, via Ponte don Melillo, 84084 Fisciano (SA), Italy;Universití di Salerno, via Ponte don Melillo, 84084 Fisciano (SA), Italy

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2012

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Abstract

One of the most challenging issues in iris recognition is the design of techniques able to ensure high accuracy even in adverse conditions. This paper deals with an approach to iris matching based on the combination of local features: Linear Binary Patterns (LBP) and discriminable textons (BLOBs) are presently exploited. The techniques have been refined ad hoc, to allow the extraction of significant discriminative features, even with images captured in variable visible light conditions, and affected by noise due to distance/resolution or to scarce user collaboration (blurring, off-axis iris, occlusion by eyelashes and eyelids). The obtained results strongly motivate further investigations along this line, most of all the addition of more local features.