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Finger Vein Image Registration Based on Genetic Algorithm

  • Zilong ChenEmail author
  • Wen Wang
  • Lijuan Sun
  • Jian Guo
  • Chong Han
  • Hengyi Ren
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 834)

Abstract

Finger vein recognition technology is an emerging biometric identification technology that utilizes the distribution structure of venous blood vessels to achieve identification. The vein recognition process is divided into two parts: registration and recognition. In the registration process, the generation of registration template is particularly important. In order to obtain the registration template more accurately, this paper proposes a finger vein image registration algorithm based on genetic algorithm. The principle of the algorithm is to use the mutual information of two finger vein images as the fitness function of the genetic algorithm, and use the genetic algorithm to search for the optimal parameters of the rigid body transformation model. The experimental results show that the algorithm is effective and can achieve the registration of finger vein images within a short iteration.

Keywords

Finger vein recognition Image registration Genetic algorithm 

Notes

Acknowledgements

This work is partly supported by the National Natural Science Foundation of China under Grant No. 61873131, 61702284 and 61572261.

References

  1. 1.
    Vakil, M.I., Malas, J.A., Megherbi, D.B.: Information theoretic approach for template matching in registration of partially overlapped aerial imagery. In: Aerospace and Electronics Conference, pp. 146–150. IEEE (2016)Google Scholar
  2. 2.
    Salhi, K., Jaara, E.M., Alaoui, M.T.: Pretreatment approaches for texture image segmentation. In: International Conference on Computer Graphics, Imaging and Visualization, pp. 221–225. IEEE (2016)Google Scholar
  3. 3.
    Tsai, C.M., Guan, S.S.: Identifying regions of interest in reading an image. Displays 39, 33–41 (2015)CrossRefGoogle Scholar
  4. 4.
    Chicotay, S., David, E., Netanyahu, N.S.: A two-phase genetic algorithm for image registration, pp. 189–190 (2017)Google Scholar
  5. 5.
    Zhang, J., Hu, J.: A novel registration method based on coevolutionary strategy. In: Evolutionary Computation, pp. 2375–2380. IEEE (2016)Google Scholar
  6. 6.
    Gou, Z., Ma, H.: An automatic registration based on genetic algorithm for multi-source remote sensing. In: International Conference on Control, Automation and Robotics, pp. 318–323. IEEE (2016)Google Scholar
  7. 7.
    Minvielle, P.: Fast Mutual information-based map model matching. In: IEEE International Geoscience and Remote Sensing Symposium. IEEE (2017)Google Scholar
  8. 8.
    Luo, H.Y.: Study on mutual information medical image registration based on ant algorithm. Int. J. Hybrid Inf. Technol. 8 (2015)CrossRefGoogle Scholar
  9. 9.
    Huang, N.: Application research of genetic algorithm image enhancement. Comput. Simul. (2012)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Zilong Chen
    • 1
    Email author
  • Wen Wang
    • 1
  • Lijuan Sun
    • 1
    • 2
  • Jian Guo
    • 1
    • 2
  • Chong Han
    • 1
    • 2
  • Hengyi Ren
    • 1
  1. 1.College of ComputerNanjing University of Posts and TelecommunicationsNanjingChina
  2. 2.Jiangsu High Technology Research Key Laboratory for Wireless Sensor NetworksNanjing University of Posts and TelecommunicationsNanjingChina

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