A Nonparametric Functional Method for Signature Recognition

Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)


We propose to use nonparametric functional data analysis techniques within the framework of a signature recognition system. Regarding the signature as a random function from \( \mathbb{R} {\rm(time \,domain)\,to}\, \mathbb{R}^2\) (position (x,y) of the pen), we tackle the problem as a genuine nonparametric functional classification problem, in contrast to currently used biometrical approaches. A simulation study on a real data set shows good results.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Fan, J., Gijbels, I.: Local PolynomialModelling and Its Applications. Chapman and Hall/CRC (1996)Google Scholar
  2. 2.
    Ferraty, F., Romain, Y.: Oxford handbook on functional data analysis (Eds). Oxford University Press (2011)Google Scholar
  3. 3.
    Ferraty, F., Vieu, P.: Nonparametric Functional Data Analysis: Theory and Practice. Springer (2006)Google Scholar
  4. 4.
    Huang, B.Q., Zhang, Y.B., Kechadi, M.T.: Preprocessing Techniques for Online Handwritting Recognition. Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications, Rio de Janeiro (2007)Google Scholar
  5. 5.
    Impedovo, D., Pirlo, G.: Automatic signature verification : The state of the art. IEEE Trans. Syst. Man. Cybern. C, Appl. Rev. 38 (5), 609–635 (2008)Google Scholar
  6. 6.
    Impedovo, S., Pirlo, G., Modugno, R., Impedovo, D., Ferrante, A., Sarcinella, L., Stasolla, E.: Advancements in Handwritting Recognition. Manuscript, Universit`a degli Studi di Bari (2010)Google Scholar
  7. 7.
    Ramsay, J.O.: Curve Registration. J. R. Stat. Soc. B 60, 351–363 (1998)MathSciNetMATHCrossRefGoogle Scholar
  8. 8.
    Ramsay, J.O.: Functional Components of Variation in Handwriting, J. Am. Stat. Assoc. 95, 9–15 (2000)CrossRefGoogle Scholar
  9. 9.
    Ramsay, J.O., Silverman, B.W.: Functional data analysis. Springer (1997)Google Scholar
  10. 10.
    Wand, M.P., Jones, M.C.: Kernel Smoothing. Chapman and Hall/CRC (1995)Google Scholar
  11. 11.
    Yeung, D.T., Chang, H., Xiong, Y., George, S., Kashi, R., Matsumoto, T., Rigoll, G.: SVC2004: First International Signature Verification Competition, Proceedings of the International Conference on Biometric Authentication (ICBA), Hong Kong (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.University of New South WalessydneyAustralia

Personalised recommendations