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Statistical Texture Analysis-Based Approach for Fake Iris Detection Using Support Vector Machines

  • Xiaofu He
  • Shujuan An
  • Pengfei Shi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

Abstract

This paper presents a novel statistical texture analysis based method for detecting fake iris. Four distinctive features based on gray level co-occurrence matrices (GLCM) and properties of statistical intensity values of image pixels are used. A support vector machine (SVM) is selected to characterize the distribution boundary, for it has good classification performance in high dimensional space. The proposed approach is privacy friendly and does not require additional hardware. The experimental results indicate the new approach to be a very promising technique for making iris recognition systems more robust against fake-iris-based spoofing attempts.

Keywords

Support Vector Machine Iris Recognition Good Classification Performance Iris Pattern Iris Database 
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 2007

Authors and Affiliations

  • Xiaofu He
    • 1
  • Shujuan An
    • 1
  • Pengfei Shi
    • 1
  1. 1.Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240China

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