Advertisement

Online Signature Verification at Sub-trajectory Level

  • Sudhir Rohilla
  • Anuj Sharma
  • R. K. Singla
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 28)

Abstract

The signatures are behavioral biometric characteristic used for authentication purpose. The verification of a signature while writing through the machine is called online signature verification. In this paper, we have implemented verification of signatures at sub-trajectory level. The verification has been performed using common threshold of features and writer dependent threshold. A set of fifty features are extracted of nature static, kinematic, statistical and structural properties. The experiments have been performed using SVC2004 (Signature Verification Competition) Task1 where forty user’s data include twenty genuine and twenty forgery signatures of each user. The achieved results indicate that verification at sub-trajectory level is a promising technique in online signature verification.

Keywords

online signature verification feature extraction feature level threshold writer dependent threshold 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Guru, D.S., Prakash, H.N.: Symbolic Representation of On-Line Signatures. In: Proceedings of International Conference Computational Intelligence and Multimedia Application, pp. 312–317 (2007)Google Scholar
  2. 2.
    Kashi, R.S., Hu, J., Nelson, W.L., Turin, W.: On-line handwritten signature verification using Hidden Markov Model features. In: International Conference on Document Analysis and Recognition, pp. 253–257 (1997)Google Scholar
  3. 3.
    Wu, Q.Z., Lee, S.Y., Jou, I.C.: On-Line Signature Verification Based on Split and Merge Matching Mechanism. Pattern Recognition Letters 18, 665–673 (1997)CrossRefGoogle Scholar
  4. 4.
    Jain, A.K., Griess, F., Colonnel, S.: On-Line Signature Verification. Pattern Recognition 35, 2963–2972 (2002)CrossRefMATHGoogle Scholar
  5. 5.
    Alister, K., Yanikoglu, B.: Identity Authentication Using Improved On-Line Signature Verification Method. Pattern Recognition Letters 26(18), 2400–2408 (2005)Google Scholar
  6. 6.
    Aguilar, J.F., Garcia, J.O., Ramos, D.D., Rodriguez, J.G.: HMM-based on-line signature verification: Feature extraction and signature modeling. Pattern Recognition Letters 28(16), 2325–2334 (2007)CrossRefGoogle Scholar
  7. 7.
    Guru, D.S., Prakash, H.N.: Online Signature Verification and Recognition: An Approach Based on Symbolic Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(6) (2009)Google Scholar
  8. 8.
    Barkoula, K., Economou, G., Fotopoulos, S.: Online signature verification based on signatures turning angle representation using longest common subsequence matching. International Journal on Document Analysis and Recognition 16(3), 261–272 (2012)CrossRefGoogle Scholar
  9. 9.
    Emerich, S., Lupu, E., Rusu, C.: A new set of features for a bimodal system based on on-line signature and speech. Digital Signal Processing 23, 928–940 (2013)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Garcia, M.L., Lara, R.R., Hurtado, O.M., Canto-Navarro, E.: Embedded System for Biometric Online Signature Verification. IEEE Transactions on Industrial Informatics 10(1), 491–501 (2014)CrossRefGoogle Scholar
  11. 11.
    Aguilar, J.F.: Adopted Fusion Schemes for Multimodal Biometric Authentication. PhD thesis, Biometric Research Lab AVTS (2006)Google Scholar
  12. 12.
    Nelson, W., Kishon, E.: Use of dynamic features for signature verification. In: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, vol. 1, pp. 201–205 (1991)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer SciencePanjab UniversityChandigarhIndia
  2. 2.Center for Advanced Study in MathematicsPanjab UniversityChandigarhIndia

Personalised recommendations