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Multimedia Tools and Applications

, Volume 71, Issue 3, pp 1411–1430 | Cite as

Toward accurate localization and high recognition performance for noisy iris images

  • Ning Wang
  • Qiong Li
  • Ahmed A. Abd El-Latif
  • Tiejun Zhang
  • Xiamu Niu
Article

Abstract

Iris recognition plays an important role in biometrics. Until now, many scholars have made different efforts in this field. However, the recognition performances of most proposed methods degrade dramatically when the image contains some noise, which inevitably occurs during image acquisition such as reflection spots, inconsistent illumination, eyelid, eyelash, hair, etc. In this paper, an accurate iris localization and high recognition performance approach for noisy iris images is presented. After filling the reflection spots using the inpainting method which is based on Navier-Stokes (NS) equations, the Probable boundary (Pb) edge detection operator is used to detect pupil edge initially, which can eliminate the interference of inconsistent illumination, eyelid, eyelash and hair. Besides, the accurate circle parameters are obtained in delicately to reduce the input space of Hough transforms. The iris feature code is constructed based on 1D Log-Gabor filter. Our thorough experimental results on the challenging iris image database CASIA-Iris-Thousand achieve an EER of 1.8272 %, which outperforms the state-of-the-art methods.

Keywords

Iris recognition Iris localization Navier-Stokes(NS) Pb edge detection Hough transforms 1D Log-Gabor 

Notes

Acknowledgements

The authors would like to thank the reviewers for their valuable comments which are greatly helpful to improve the clarity and quality of this work. This work is supported by the National Natural Science Foundation of China (Grant Number: 60832010, 61100187) and the Fundamental Research Funds for the Central Universities (Grant Number: HIT. NSRIF. 2010046, HIT. NSRIF. 2013061).

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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Ning Wang
    • 1
  • Qiong Li
    • 1
  • Ahmed A. Abd El-Latif
    • 1
    • 2
  • Tiejun Zhang
    • 1
  • Xiamu Niu
    • 1
  1. 1.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina
  2. 2.Mathematics Department, Faculty of ScienceMenoufia UniversityShebin El-KoomEgypt

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