Writer Identification Using Super Paramagnetic Clustering and Spatio Temporal Neural Network

  • Seyyed Ataollah Taghavi Sangdehi
  • Karim Faez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)


This paper discusses use of Super Paramagnetic Clustering (SPC) and Spatio Temporal Artificial Neuron in on-line writer identification, on Farsi handwriting. In online cases, speed and automation are advantages of one method on others, therefore we used unsupervised and relatively quick clustering method, which in comparison with conventional approaches, give us better result. Moreover, regardless of various parameters that available from acquisition systems, we only consider to displacement of pen tip at determined direction that lead to quick system due to its quick preprocessing and clustering. Also we use a threshold that remove displacement between disconnected point of a word that lead to a better classification result on on-line Farsi writers.


Writer Identification Super Paramagnetic Clustering Spatio Temporal Neural Network 


  1. 1.
    Gupta, S.: Automatic Person Identification and Verification using Online Handwriting, thesis,Hyderabad, INDIA (2008)Google Scholar
  2. 2.
    Faundez-Zanuy, M.: On-line signature recognition based on VQ-DTW. Pattern Recognition 40, 981–992 (2007)zbMATHCrossRefGoogle Scholar
  3. 3.
    Kashi, R., Hu, J., Nelson, W.L.: A Hidden Markov Model approach to online handwritten signature verification. IJDAR 1, 102–109 (1998)CrossRefGoogle Scholar
  4. 4.
    Thumwarin, P., Tangtisanon, P., Murata, S., Matsuura, T.: On-line Writer Recognition for Thai Numeral. In: Proc. IEEE Circuits and Systems, Asia-pacific Conference, pp. 503–508 (2002)Google Scholar
  5. 5.
    Thumwarin, P., Matsuura, T.: On-line Writer Recognition for Thai Based on Velocity of Barycenter of Pen-point Movement. In: ICIP, pp. 889–892 (2004)Google Scholar
  6. 6.
    Hangai, S., Yamanaka, S., Hamamoto, T.: On-line Signature Verification Based On Altitude and Direction of Pen Movement. In: ICME, pp. 489–492 (2000)Google Scholar
  7. 7.
    Blatt, M., Wiseman, S., Domany, E.: Super Paramagnetic Clustering of Data. Phys. Rev. Lett. 76, 3251–3254 (1996)CrossRefGoogle Scholar
  8. 8.
    Wolf, U.: Comparison Between Cluster Montecarlo algorithm in the Ising spin model. Phys.Lett.B 228, 379–382 (1989)CrossRefGoogle Scholar
  9. 9.
    Quiroga, Q., Nadasty, R., Ben-Shaul, Z.: Unsupervised Spike Detection and Sorting With Wavelets and Superparamagnetic Clustering. Neural Computation 16, 1661–1687 (2004)zbMATHCrossRefGoogle Scholar
  10. 10.
    Baig, R.: Spatial-Temporal Artificial Neurons Applied to On-line Cursive Handwritten Character Recognition. In: ESANN, pp. 561–566 (2004)Google Scholar
  11. 11.
    Baig, R., Hussain, M.: On-line Signture Recognition and Writer Identification Using Spatial-Temporal Processing. In: INMIC, pp. 381–385 (2004)Google Scholar
  12. 12.
    Li, B., Zhang, D., Wang, K.: Online signature verification based on null component analysis and principal component analysis. Pattern anal. applic., 345–356 (2005)Google Scholar
  13. 13.
    Zhang, K., Nyssen, E., Sahli, H.: A Multi-Stage Online Signature Verification System. Pattern Analysis & Application (5), 288–295 (2002)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Seyyed Ataollah Taghavi Sangdehi
    • 1
  • Karim Faez
    • 1
  1. 1.Qazvin Azad University of Iran, Amirkabir UniversityTehranIran

Personalised recommendations