Iris Anti-spoofing

  • Zhenan SunEmail author
  • Tieniu Tan
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)


Iris images contain rich texture information for reliable personal identification. However, forged iris patterns may be used to spoof iris recognition systems. This paper proposes an iris anti-spoofing approach based on the texture discrimination between genuine and fake iris images. Four texture analysis methods include gray level co-occurrence matrix, statistical distribution of iris texture primitives, local binary patterns (LBP) and weighted-LBP are used for iris liveness detection. And a fake iris image database is constructed for performance evaluation of iris liveness detection methods. Fake iris images are captured from artificial eyeballs, textured contact lens and iris patterns printed on a paper, or synthesised from textured contact lens patterns. Experimental results demonstrate the effectiveness of the proposed texture analysis methods for iris liveness detection. And the learned statistical texture features based on weighted-LBP can achieve 99accuracy in classification of genuine and fake iris images.


Local Binary Pattern Iris Image Sift Descriptor Iris Recognition Local Binary Pattern Feature 
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.


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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern RecognitionInstitute of Automation, Chinese Academy of SciencesBeijingP.R. China

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