Design Decisions for an Iris Recognition SDK

  • Christian RathgebEmail author
  • Andreas Uhl
  • Peter Wild
  • Heinz Hofbauer
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)


Open-source software development kits are vital to (iris) biometric research in order to achieve comparability and reproducibility of research results. In addition, for further advances in the field of iris biometrics the community needs to be provided with state-of-the-art reference systems, which serve as adequate starting point for new research. This chapter provides a summary of relevant design decisions for software modules constituting an iris recognition system. The proposal of general criteria and adequate concepts is complemented by a detailed description of how according design decisions are implemented in the University of Salzburg Iris Toolkit, an open-source iris recognition software which contains diverse algorithms for iris segmentation, feature extraction, and comparison. Building upon a file-based processing chain, the provided open-source software is designed to support rapid prototyping as well as integration in existing frameworks achieving enhanced usability and extensibility. In order to underline the competitiveness of the presented iris recognition software, experimental evaluations of segmentation and feature extraction algorithms are carried out on a publicly available iris database and compared to a commercial product.


Local Binary Pattern Scale Invariant Feature Transform Iris Image Biometric System Iris Recognition 
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.



This work was partially supported by the European FP7 FIDELITY project (SEC-2011-284862), the Center for Advanced Security Research Darmstadt (CASED) and the Austrian Science Fund, project no. P26630.


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Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  • Christian Rathgeb
    • 1
    Email author
  • Andreas Uhl
    • 2
  • Peter Wild
    • 3
  • Heinz Hofbauer
    • 2
  1. 1.Biometrics and Internet Security Research GroupHochschule DarmstadtDarmstadtGermany
  2. 2.Multimedia Signal Processing and Security Lab, Department of Computer SciencesUniversity of SalzburgSalzburgAustria
  3. 3.Safety and Security DepartmentAIT Austrian Institute of Technology GmbHSeibersdorfAustria

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