A New Fake Iris Detection Method

  • Xiaofu He
  • Yue Lu
  • Pengfei Shi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

Recent research works have revealed that it is not difficult to spoof an automated iris recognition system using fake iris such as contact lens and paper print etc. Therefore, it is very important to detect fake iris as much as possible. In this paper, we propose a new fake iris detection method based on wavelet packet transform. First, wavelet packet decomposition is used to extract the feature values which provide unique information for discriminating fake irises from real ones. Second, to enhance the detecting accuracy of fake iris, Support vector machine (SVM) is used to characterize the distribution boundary based on extracted wavelet packet features, for it has good classification performance in high dimensional space and it is originally developed for two-class problems. The experimental results indicate the proposed method is to be a very promising technique for making iris recognition systems more robust against fake iris spoofing attempts.

Keywords

Support Vector Machine Wavelet Packet Iris Image Correct Classification Rate 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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Xiaofu He
    • 1
  • Yue Lu
    • 1
  • Pengfei Shi
    • 2
  1. 1.Department of Computer Science and TechnologyEast China Normal UniversityShanghaiChina
  2. 2.Institute of Image Processing and Pattern RecognitionShanghai Jiao Tong UniversityShanghaiChina

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