Robust and Fast Assessment of Iris Image Quality

  • Zhuoshi Wei
  • Tieniu Tan
  • Zhenan Sun
  • Jiali Cui
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)

Abstract

Iris recognition is one of the most reliable methods for personal identification. However, not all the iris images obtained from the device are of high quality and suitable for recognition. In this paper, a novel approach for iris image quality assessment is proposed to select clear images in the image sequence. The proposed algorithm uses three distinctive features to distinguish three kinds of poor quality images, i.e. defocus, motion blur and occlusion. Experimental results demonstrate the effectiveness of the algorithm. Clear iris images selected by our method are essential to subsequent iris recognition.

Keywords

Iris Image Clear Image Convolution Kernel Poor Quality Image Motion Blur 
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 2005

Authors and Affiliations

  • Zhuoshi Wei
    • 1
  • Tieniu Tan
    • 1
  • Zhenan Sun
    • 1
  • Jiali Cui
    • 1
  1. 1.Institute of Automation, Chinese Academy of SciencesNational Laboratory of Pattern RecognitionBeijingP.R. China

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