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Chinese Conference on Biometric Recognition

CCBR 2017: Biometric Recognition pp 383–390Cite as

Iris Recognition Based on Adaptive Gabor Filter

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10568))

Abstract

Aiming at the problem of multi-category iris recognition, there proposes a method of iris recognition algorithm based on adaptive Gabor filter. Use DE-PSO to adaptive optimize the Gabor filter parameters. DE-PSO is composed of particle swarm optimization and differential evolution algorithm. Use 16 groups of 2D-Gabor filters with different frequencies and directions to process iris images. According to the direction and frequency of maximum response amplitude, transform iris features into 512-bit binary feature encoding. Calculate the Hamming distance of feature code and compare with the classification threshold, determine iris the type of iris. Experiment on a variety of iris databases with multiple Gabor filter algorithms, the results showed that this algorithm has higher recognition rate, the ROC curve is closer to the coordinate axis and the robustness is better, compare with other Gabor filter algorithm.

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Acknowledgments

The authors would like to thank the referee’s advice and acknowledge the support of the National Natural Science Foundation of China (NSFC) under Grant No. 61471181, Natural Science Foundation of Jilin Province under Grant Nos. 20140101194JC, 20150101056JC.

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Authors and Affiliations

  1. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, Jilin, China

    Shuai Liu, Yuanning Liu, Xiaodong Zhu, Jingwei Cui & Yihao Chen

  2. School of Software, Jilin University, Changchun, 130012, Jilin, China

    Shuai Liu & Jingwei Cui

  3. School of Computer Science and Technology, Jilin University, Changchun, 130012, Jilin, China

    Yuanning Liu, Xiaodong Zhu & Yihao Chen

  4. Informatization Office, Northeast Electric Power University, Jilin, 132012, China

    Guang Huo

Authors
  1. Shuai Liu
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  2. Yuanning Liu
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  3. Xiaodong Zhu
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  4. Guang Huo
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  5. Jingwei Cui
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  6. Yihao Chen
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Corresponding author

Correspondence to Xiaodong Zhu .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Zhou

  2. Beihang University, Beijing, China

    Yunhong Wang

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Computing and Technology, Chinese Academy of Sciences, Beijing, China

    Yong Xu

  5. Shenzhen University, Shenzhen, China

    Linlin Shen

  6. Tsinghua University, Beijing, China

    Jianjiang Feng

  7. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  8. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yu Qiao

  9. Graduate School at Shenzhen, Tsinghua University, Shenzhen, China

    Zhenhua Guo

  10. Shenzhen University, Shenzhen, China

    Shiqi Yu

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Cite this paper

Liu, S., Liu, Y., Zhu, X., Huo, G., Cui, J., Chen, Y. (2017). Iris Recognition Based on Adaptive Gabor Filter. In: Zhou, J., et al. Biometric Recognition. CCBR 2017. Lecture Notes in Computer Science(), vol 10568. Springer, Cham. https://doi.org/10.1007/978-3-319-69923-3_41

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  • DOI: https://doi.org/10.1007/978-3-319-69923-3_41

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69922-6

  • Online ISBN: 978-3-319-69923-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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