A New Fake Iris Detection Method

  • Authors:

  • Xiaofu He;Yue Lu;Pengfei Shi

  • Affiliations:

  • Department of Computer Science and Technology, East China Normal University, Shanghai, China 200241;Department of Computer Science and Technology, East China Normal University, Shanghai, China 200241;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China 200240

  • Venue:
  • ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
  • Year:
  • 2009

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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.