Similarity Measurement for Off-Line Signature Verification

  • Xinge You
  • Bin Fang
  • Zhenyu He
  • Yuanyan Tang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3644)


Existing methods to deal with off-line signature verification usually adopt the feature representation based approaches which suffer from limited training samples. It is desired to employ straightforward means to measure similarity between 2-D static signature graphs. In this paper, we incorporate merits of both global and local alignment methods. Two signature patterns are globally registered using weak affine transformation and correspondences of feature points between two signature patterns are determined by applying an elastic local alignment algorithm. Similarity is measured as the mean square of sum Euclidean distances of all found corresponding feature points based on a match list. Experimental results showed that the computed similarity measurement was able to provide sufficient discriminatory information. Verification performance in terms of equal error rate was 18.6% with four training samples.


Training Sample Feature Point Signature Pattern Equal Error Rate Signature Verification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Plamondon, R., Srihari, S.N.: On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(1), 63–84 (2000)CrossRefGoogle Scholar
  2. 2.
    Ammar, M.: Progress in Verification of Skillfully Simulated Handwritten Signatures. Int. J. Pattern Recognition and Artificial Intelligence 5(1), 337–351 (1991)CrossRefGoogle Scholar
  3. 3.
    Sabourin, R., Genest, G., Prêteux, F.: Off-line Signature Verification by Local Granulometric Size Distributions. IEEE Trans. Pattern Analysis and Machine Intelligence 19(9), 976–988 (1997)CrossRefGoogle Scholar
  4. 4.
    Sabourin, R., Genest, G.: An Extended-shadow-code-based Approach for Off-line Signature Verification. Part I. Evaluation of The Bar Mask Definition. In: Proc. Int. Conference on Pattern Recognition, pp. 450–453 (1994)Google Scholar
  5. 5.
    Raudys, S.J., Jain, A.K.: Small Sample Size Effects in Statistical Pattern Recognition. IEEE Tran. Pattern Recognition and Machine Intelligence 13(3), 252–264 (1991)CrossRefGoogle Scholar
  6. 6.
    Fukunaga, K.: Introduction to Statistical Pattern Recognition, 2nd edn. Academic Press, Boston (1990)zbMATHGoogle Scholar
  7. 7.
    Murshed, N., Sabourin, R., Bortolozzi, F.: A Cognitive Approach to Off-line Signature Verification. Automatic Bankcheck Processing. World Scientific Publishing Co., Singapore (1997)Google Scholar
  8. 8.
    O’Sullivan, F.: A Statistical Perspective on Ill-posed Inverse Problems. Statistical Science, 502–527 (1986)Google Scholar
  9. 9.
    Fang, B., Tang, Y.Y.: Reduction of Feature Statistics Estimation Error for Small Training Sample Size in Off-line Signature Verification. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 526–532. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  10. 10.
    Qi, Y., Hunt, B.R.: Signature Verification Using Global and Grid Features. Pattern Recognition 27(12), 1621–1629 (1994)CrossRefGoogle Scholar
  11. 11.
    Sabourin, R., Genest, G., Prêteux, F.: Off-line Signature Verification by Local Granulometric Size Distributions. IEEE Trans. Pattern Analysis and Machine Intelligence 19(9), 976–988 (1997)CrossRefGoogle Scholar
  12. 12.
    Fang, B., Leung, C.H., Tang, Y.Y., Tse, K.W., Kwok, P.C.K., Wong, Y.K.: Offline signature verification by the tracking of feature and stroke positions. Pattern Recognition 36(1), 91–101 (2003)zbMATHCrossRefGoogle Scholar
  13. 13.
    Borgefors, G.: Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm. IEEE Trans. Pattern Analysis Machine Intelligence 10(6), 849–865 (1988)CrossRefGoogle Scholar
  14. 14.
    Leung, C.H., Suen, C.Y.: Matching of Complex Patterns by Energy Minimization. IEEE Transactions on Systems, Man and Cybernetics, Part B 28(5), 712–720 (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xinge You
    • 1
    • 3
  • Bin Fang
    • 2
    • 3
  • Zhenyu He
    • 3
  • Yuanyan Tang
    • 1
    • 3
  1. 1.Faculty of Mathematics and Computer ScienceHubei UniversityChina
  2. 2.Center for Intelligent Computation of InformationChongqing UniversityChongqingChina
  3. 3.Department of Computer ScienceHong Kong Baptist University 

Personalised recommendations