Skip to main content
SpringerLink
Log in

On the Use of First and Second Derivative Approximations for Biometric Online Signature Recognition

  • Conference paper
  • First Online:
Advances in Computational Intelligence (IWANN 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14134))

Included in the following conference series:

Abstract

This paper investigates the impact of different approximation methods in feature extraction for pattern recognition applications, specifically focused on delta and delta-delta parameters. Using MCYT330 online signature database, our experiments show that 11-point approximation outperforms 1-point approximation, resulting in a 1.4% improvement in identification rate, 36.8% reduction in random forgeries and 2.4% reduction in skilled forgeries.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Faundez-Zanuy, M.: Biometric security technology. IEEE Aerosp. Electron. Syst. Mag. 21(6), 15–26 (2006). https://doi.org/10.1109/MAES.2006.1662038

    Article  Google Scholar 

  2. Faundez-Zanuy, M., Fierrez, J., Ferrer, M.A., et al.: Handwriting biometrics: applications and future trends in e-security and e-health. Cogn. Comput. 12, 940–953 (2020). https://doi.org/10.1007/s12559-020-09755-z

    Article  Google Scholar 

  3. Faundez-Zanuy, M., Mekyska, J., Impedovo, D.: Online handwriting, signature and touch dynamics: tasks and potential applications in the field of security and health. Cogn. Comput. 13, 1406–1421 (2021). https://doi.org/10.1007/s12559-021-09938-2

    Article  Google Scholar 

  4. Ortega-Garcia J., et al.: MCYT baseline corpus: a bimodal biometric database. IEE Proc. Vis. Image Sign. Process. 150(6), 395–401 (2003). https://doi.org/10.1049/ip-vis:20031078

  5. Faundez-Zanuy, M.: On-line signature recognition based on VQ-DTW. Pattern Recogn. 40(3), 981–992 (2007). ISSN 0031–3203, https://doi.org/10.1016/j.patcog.2006.06.007

  6. Martin, A., Doddington, G., Kamm, T., Ordowski, M., Przybocki, M.: The det curve in assessment of detection performance. In: Proceedings of the European Conference on Speech Communication and Technology, pp. 1895–1898 (1997)

    Google Scholar 

  7. https://www.nist.gov/itl/iad/mig/tools

  8. Fischer, A., Diaz, M., Plamondon, R., Ferrer, M.A.: Robust score normalization for DTW-based online signature verification. In: 2015 13th International Conference on Document Analysis and Recognition (ICDAR), Tunis, Tunisia, pp. 241–245 (2015). https://doi.org/10.1109/ICDAR.2015.7333760

  9. Rabiner, L.R., Schafer, R.W.: Theory and Applications of Digital Speech Processing. Upper Saddle River, NJ: Pearson (2010)

    Google Scholar 

  10. Mucha, J., et al.: Identification and monitoring of Parkinson’s disease dysgraphia based on fractional-order derivatives of online handwriting. Appl. Sci. 8, 2566 (2018). https://doi.org/10.3390/app8122566

    Article  Google Scholar 

  11. Mucha, J., et al.: Fractional derivatives of online handwriting: a new approach of parkinsonic dysgraphia analysis. In: 2018 41st International Conference on Telecommunications and Signal Processing (TSP), Athens, Greece, pp. 1–4 (2018). https://doi.org/10.1109/TSP.2018.8441293

  12. Mucha, J., et al.: Analysis of Parkinson’s disease dysgraphia based on optimized fractional order derivative features. In: 2019 27th European Signal Processing Conference (EUSIPCO), A Coruna, Spain, pp. 1-5 (2019).https://doi.org/10.23919/EUSIPCO.2019.8903088

  13. Deller, J.R., Proakis, J.G., Hansen, J.H.L.: Dynamic time warping. In: Discrete-time processing of speech signals, New York: Macmillan Publishing Co. (1993)

    Google Scholar 

  14. Diaz, M., Ferrer, M.A., Impedovo, D., Malik, M.I., Pirlo, G., Plamondon, R.: A perspective analysis of handwritten signature technology. Acm Comput. Surv. (Csur) 51(6), 1–39 (2019)

    Article  Google Scholar 

  15. Kholmatov, A., Yanikoglu, B.: Identity authentication using improved online signature verification method. Pattern Recogn. Lett. 26(15), 2400–2408 (2005)

    Article  Google Scholar 

  16. Sae-Bae, N., Memon, N.: Online signature verification on mobile devices. IEEE Trans. Inf. Forensics Secur. 9(6), 933–947 (2014)

    Article  Google Scholar 

  17. Tolosana, R., et al.: ICDAR 2021 competition on on-line signature verification. In: Lladós, J., Lopresti, D., Uchida, S. (eds.) ICDAR 2021. LNCS, vol. 12824, pp. 723–737. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-86337-1_48

  18. Jiang, J., Lai, S., Jin, L., Zhu, Y.: DsDTW: local representation learning with deep soft-DTW for dynamic signature verification. IEEE Trans. Inf. Forensics Secur. 17, 2198–2212 (2022)

    Article  Google Scholar 

  19. Diaz, M., Ferrer, M.A., Quintana, J.J.: Robotic arm motion for verifying signatures. In: 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 157–162. IEEE (2018)

    Google Scholar 

Download references

Acknowledgments

This work has been supported by MINECO Spanish grant number PID2020-113242RB-I00, and PID2019-109099RB-C41.

Author information

Authors and Affiliations

  1. Tecnocampus, Universitat Pompeu Fabra, 08302, Mataró, Spain

    Marcos Faundez-Zanuy

  2. Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Moises Diaz

Authors
  1. Marcos Faundez-Zanuy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Moises Diaz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marcos Faundez-Zanuy .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Malaga, Málaga, Spain

    Gonzalo Joya

  3. Polytechnic University of Catalonia, Vilanova i la Geltrú, Spain

    Andreu Catala

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Faundez-Zanuy, M., Diaz, M. (2023). On the Use of First and Second Derivative Approximations for Biometric Online Signature Recognition. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2023. Lecture Notes in Computer Science, vol 14134. Springer, Cham. https://doi.org/10.1007/978-3-031-43085-5_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-43085-5_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43084-8

  • Online ISBN: 978-3-031-43085-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation