Robust and fast assessment of iris image quality

Authors:
Zhuoshi Wei;Tieniu Tan;Zhenan Sun;Jiali Cui
Affiliations:
Institute of Automation, Chinese Academy of Sciences, National Laboratory of Pattern Recognition, Beijing, P.R. China;Institute of Automation, Chinese Academy of Sciences, National Laboratory of Pattern Recognition, Beijing, P.R. China;Institute of Automation, Chinese Academy of Sciences, National Laboratory of Pattern Recognition, Beijing, P.R. China;Institute of Automation, Chinese Academy of Sciences, National Laboratory of Pattern Recognition, Beijing, P.R. China
Venue:
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Year:
2006

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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.