A New Approach to Signature-Based Authentication

  • Georgi Gluhchev
  • Mladen Savov
  • Ognian Boumbarov
  • Diana Vasileva
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

Abstract

A new signature based authentication approach is described, where signing clips are analyzed. Using an web-camera a series of frames is acquired that allows investigating the dynamics of the complex “hand-pen”. For this a set of features of the hand, the pen and their mutual disposition at the time of signing is derived. Classification and verification decision-making rule based on the Mahalanobis distance has been used. A class-related feature weighting is proposed for the improvement of accuracy. A Gaussian-based model for the description of skin color is suggested. The preliminary experimental results have confirmed the reliability of the approach.

Keywords

Signature Authentication Biometrics Feature weight Classifica-tion error Color modeling 

References

  1. 1.
    Bouguila, N., Ziou, D.: Dirichlet-based probability model applied to human skin detection. In: Proc. Int. Conf. ASSP 2004, vol. V, pp. 521–524 (2004)Google Scholar
  2. 2.
    Boumbarov, O., Vassileva, D., Muratovski, K.: Face extraction using 2D color histograms. In: ICEST 2005. XL Int. Scientific Conf. on Information, Communication and Energy Systems and Technologies, Nis, Serbia and Montenegro, vol. 1, pp. 334–337 (2005)Google Scholar
  3. 3.
    Fang, B., Leung, C.H., Tang, Y.Y., Kwok, P.C.K., Tse, K.W., Wong, Y.K.: Off-line signature verification with generated training samples. IEE Proc. Vis. Image Signal Process 149(2), 85–90 (2002)CrossRefGoogle Scholar
  4. 4.
    Fink, G., Wienecke, M., Sagerer, G.: Video-Based On-Line Handwriting Recognition. In: Proc. Int. Conf. on Document Analysis and Recognition, pp. 226–230. IEEE, Los Alamitos (2001)CrossRefGoogle Scholar
  5. 5.
    Fu, Z., Yang, J., Hu, W., Tan, T.: Mixture clustering using multidimensional histograms for skin detection. In: ICPR 2004. Proc. of the 17th Int. Conf. on Pattern Recognition, pp. 549–552 (2004)Google Scholar
  6. 6.
    Hairong, L., Wenyuan, W., Chong, W., Quing, Z.: Off-line Chinese signature verification based on support vector machines. Pattern Recognition Letters 26, 2390–2399 (2005)CrossRefGoogle Scholar
  7. 7.
    Ismail, M.A., Gad, S.: Off-line arabic signature recognition and verification. Pattern Recognition 33, 1727–1740 (2000)CrossRefGoogle Scholar
  8. 8.
    Jain, A.K., Griess, F.D., Connell, S.D.: On-Line Signature Verification. Pattern Recognition 35(12), 2963–2972 (2002)MATHCrossRefGoogle Scholar
  9. 9.
    Ka, H., Yan, H.: Off-line signature verification based on geometric feature extraction and neural network classification. Pattern Recognition 30(1), 9–17 (1996)Google Scholar
  10. 10.
    Kai, H., Yan, H.: Off-line signature verification using structural feature correspondence. Pattern Recognition 35, 2467–2477 (2002)MATHCrossRefGoogle Scholar
  11. 11.
    Kuckuk, W., Rieger, B., Steinke, K.: Automatic Writer Recognition. In: Proc. of Carnahan Conf. on Crime Countermeasures, Kentuky, pp. 57–64 (1979)Google Scholar
  12. 12.
    Lantzman, R.: Cybernetics and forensic handwriting investigation, Nauka, Moscow (1968)Google Scholar
  13. 13.
    Munich, M.E., Perona, P.: Camera-Based ID Verification by Signature Tracking. In: Proc. of 5th European Conference on Computer Vision ECCV 1998, Freiburg, Germany, pp. 782–796 (1998)Google Scholar
  14. 14.
    Nalimov, V.V., Chernova, N.A.: Statistical Methods in Experiment Planning, Nauka, Moskow (1965)Google Scholar
  15. 15.
    Savov, M., Gluhchev, G.: Automated Signature Detection from Hand Movement. In: Proc. of CompSysTech 2004, Rousse, Bulgaria, pp. III.A.3-1–III.A.3-6 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Georgi Gluhchev
    • 1
  • Mladen Savov
    • 1
  • Ognian Boumbarov
    • 2
  • Diana Vasileva
    • 2
  1. 1.Institute of Information Technologies,2 Acad. G. Bonchev Str., Sofia 1113Bulgaria
  2. 2.Faculty of Communication Technologies, Technical University, 8, Kl. Ohridski, 1000 SofiaBulgaria

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