A Two-Stage Approach for English and Hindi Off-line Signature Verification

  • Srikanta Pal
  • Umapada Pal
  • Michael Blumenstein
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8158)


The purpose of this paper is to present an empirical contribution towards the understanding of multi-script off-line signature identification and verification using a novel method involving off-line Hindi (Devnagari) and English signatures. The main aim of this approach is to demonstrate the significant advantage of the use of signature script identification in a multi-script signature verification environment. In the 1st stage of the proposed signature verification technique a script identification technique is employed to know whether a signature is written in Hindi or English. In the second stage, a verification approach was explored separately for English signatures and Hindi signatures based on the script identification result. Different features like gradient feature, water reservoir feature, loop feature, aspect ratio etc. were employed, and Support Vector Machines (SVMs) were considered in our scheme. To get the comparative idea, multi-script signature verification results on the joint Hindi and English dataset without using any script identification technique is also computed. From the experiment results it is noted that we are able to reduce average error rate 4.81% more when script identification method is employed.


  1. 1.
    Madabusi, S., Srinivas, V., Bhaskaran, S., Balasubramanian, M.: On-line and off-line signature verification using relative slope algorithm. In: International Workshop on Measurement Systems for Homeland Security, pp. 11–15 (2005)Google Scholar
  2. 2.
    Kalera, M., Srihari, S., Xu, A.: Offline signature verification and identification using distance statistics. International Journal on Pattern Recognition and Artificial Intelligence, 1339–1360 (2004)Google Scholar
  3. 3.
    Plamondon, R., Lorette, G.: Automatic signature verification and writer identification - the state of the art. Pattern Recognition, 107–131 (1989)Google Scholar
  4. 4.
    Pal, S., Alaei, A., Pal, U., Blumenstein, M.: Off-line signature identification using background and foreground information. In: International Conference on Digital Image Computing, pp. 672–677 (2011)Google Scholar
  5. 5.
    Pal, S., Alaei, A., Pal, U., Blumenstein, M.: Multi-Script off-line signature identification. In: 12th International Conference on Hybrid Intelligent Systems, pp. 236–240 (2012)Google Scholar
  6. 6.
    Pal, S., Pal, U., Blumenstein, M.: Hindi and English off-line signature identification and verification. In: International Conference on Advances in Computing, pp. 905–910 (2012)Google Scholar
  7. 7.
    Impedovo, D., Pirlo, G.: Automatic Signature Verification: The State of the Art. IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews 38, 609–635 (2008)CrossRefGoogle Scholar
  8. 8.
    Ferrer, M.A., Alonso, J.B., Travieso, C.M.: Offline geometric parameters for automatic signature verification using fixed-point arithmetic. IEEE PAMI 27, 993–997 (2005)CrossRefGoogle Scholar
  9. 9.
    Ito, T., Ohyama, W., Wakabayashi, T., Kimura, F.: Combination of signature verification techniques by SVM. In: International Conference on Frontiers in Handwriting Recognition, pp. 428–431 (2012)Google Scholar
  10. 10.
    Pal, U., Belaid, A., Choisy, C.: Touching numeral segmentation using water reservoir concept. Pattern Recognition Letters 24(1-3), 261–272 (2003)CrossRefGoogle Scholar
  11. 11.
    Schafer, B., Viriri, S.: An off-Line signature verification system. In: International Conference on Signal and Image Processing Applications, pp. 95–100 (2009)Google Scholar
  12. 12.
    Tarafdar, A., Mandal, R., Pal, S., Pal, U., Kimura, F.: Shape code based word-image matching for retrieval of Indian multi-lingual documents. In: ICPR, pp. 1989–1992 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Srikanta Pal
    • 1
  • Umapada Pal
    • 2
  • Michael Blumenstein
    • 1
  1. 1.School of Information and Communication TechnologyGriffith UniversityAustralia
  2. 2.Computer Vision and Pattern Recognition UnitIndian Statistical InstituteIndia

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