Statistical Displacement Analysis for Handwriting Verification

  • Yoshiki Mizukami
  • Katsumi Tadamura
  • Mitsu Yoshimura
  • Isao Yoshimura
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)


In this paper, it is assumed that each writer has his or her own statistics of handwriting displacement, therefore a statistical displacement analysis for handwriting verification is proposed. Here, a regularization method with the coarse-to-fine strategy computes the displacement function in questionable handwritten letters, and then it is normalized to remove the noisy displacement that arises from the position drift and scaling variation. Finally, the normalized displacement function and the statistics of displacement obtained in advance from registered authentic letters are used to calculate the distance from a standard handwritten letter to a questionable one. A fundamental simulation was conducted in order to evaluate the performance of the proposed method.


  1. 1.
    Plamondon, R., Lorette, G.: Automatic signature verification and writer identification – the state of the art. Pattern Recognition 22(2), 107–131 (1989)CrossRefGoogle Scholar
  2. 2.
    de Bruyne, P., Forré, R.: Signature verification with elastic image matching. In: Proc. International Carnahan Conference on Security and Technology, pp. 113–118 (1986)Google Scholar
  3. 3.
    Naske, R.-D.: Writer recognition by prototype related deformation of handprinted characters. In: Proc. 6-th International Conference on Pattern Recognition, vol. 2, pp. 819–822 (1982)Google Scholar
  4. 4.
    Mizukami, Y., Yoshimura, M., Miike, H., Yoshimura, I.: An off-line signature verification system using an extracted displacement function. In: Proc. 5th ICDAR, vol. 1, pp. 757–760 (1999)Google Scholar
  5. 5.
    Poggio, T., Torre, V., Koch, C.: Computational vision and regularization theory. NATURE 317(6035), 314–319 (1985)CrossRefGoogle Scholar
  6. 6.
    March, R.: Computation of stereo disparity using regularization. Pat. Recog. Let. 8(3), 181–188 (1988)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Mizukami, Y.: A handwritten Chinese character recognition system using hierarchical displacement extraction based on directional features. Pattern Recognition Letters 19(7), 595–604 (1998)zbMATHCrossRefGoogle Scholar
  8. 8.
    Horn, B., Schunck, B.: Determining optical flow. Artificial Intelligence 17, 185–203 (1981)CrossRefGoogle Scholar
  9. 9.
    Yoshimura, I., Yoshimura, M.: Off-line verification of Japanese signature after elimination of background patterns. International Journal of Pattern Recognition and Artificial Intelligence 8(3), 693–708 (1994)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yoshiki Mizukami
    • 1
  • Katsumi Tadamura
    • 1
  • Mitsu Yoshimura
    • 2
  • Isao Yoshimura
    • 3
  1. 1.Yamaguchi University 
  2. 2.Ritsumeikan University 
  3. 3.Tokyo Science University 

Personalised recommendations