Iris Spoofing: Reverse Engineering the Daugman Feature Encoding Scheme

  • Shreyas Venugopalan
  • Marios Savvides
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)


Biometric systems based on iridal patterns have shown very high accuracies in verifying an individual’s identity due to the uniqueness of the iris pattern across individuals. For identity verification purposes, only the iris bit code template of an individual need be stored. In this chapter, we explore methods to generate synthetic iris textures corresponding to a given person for the purpose of bypassing an iris-based security system using these iris templates. We present analysis to prove that when this “spoof” texture is presented to an iris recognition system; it will elicit a similar response from the system as that due to the genuine iris texture to which the spoof corresponds. We embed this spoof texture within the iris of an imposter to achieve this end. Systems using filter-based feature extraction systems – such as Daugman style systems – may be bypassed using this technique. We assume knowledge of solely the feature extraction mechanism of the iris matching scheme and, as mentioned, the iris bit code template of the person whose iris is to be spoofed. We present a complete investigation into how one can get by an iris recognition system using this approach, by generating various “natural”-looking irises and hope to use this knowledge to incorporate several countermeasures into the feature extraction scheme of an iris recognition module.


Receiver Operating Characteristic Curve Iris Image Iris Recognition Gabor Function Background Texture 
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 research was supported by CyLab at Carnegie Mellon under grants DAAD19-02-1-0389 and W911NF-09-1-0273 from the Army Research Office.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Cylab Biometrics Center, Department of Electrical and Computer EngineeringCarnegie Mellon UniversityPittsburghUSA

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