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Handwritten Signature Verification: The State of the Art

  • Anastasia Beresneva
  • Anna Epishkina
  • Sergey Babkin
  • Alexey Kurnev
  • Vladimir Lermontov
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 636)

Abstract

Nowadays handwritten signature and its verification is utilized in a lot of applications including e-commerce. An analysis of verification algorithms and areas of their practical usage is provided. The focus of the investigation is on verification method based on neural network. This type of verification algorithm is realized as a mobile application and its main characteristics are obtained. The directions of further work are concluded including a modification of an algorithm and its realization in order to remove its disadvantages.

Keywords

Handwritten signature Verification Neural network Mobile application 

Notes

Acknowledgments

Authors acknowledge support from the MEPhI Academic Excellence Project (Contract No. 02.a03.21.0005).

References

  1. 1.
    Kashi, R.S., Hu, J., Nelson, W.L., Turin, W.: On-line handwritten signature verification using hidden markov model features. In: IEEE Proceedings 4th International Conference Document Analysis and Recognition, pp. 253–257 (1997)Google Scholar
  2. 2.
    McCabe, A., Trevathan, J., Read, W.: Neural network-based handwritten signature verification. J. Comput. 3(8), 9–22 (2008)CrossRefGoogle Scholar
  3. 3.
    Beatrice, D., Thomas, H.: On-line handwritten signature verification using machine learning techniques with a deep learning approach. Master’s Theses in Mathematical Sciences (2015)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Anastasia Beresneva
    • 1
  • Anna Epishkina
    • 1
  • Sergey Babkin
    • 1
  • Alexey Kurnev
    • 1
  • Vladimir Lermontov
    • 1
  1. 1.National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)MoscowRussia

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