Tamil Handwriting Recognition Using Subspace and DTW Based Classifiers

  • Niranjan Joshi
  • G. Sita
  • A. G. Ramakrishnan
  • Sriganesh Madhvanath
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)

Abstract

In this paper, we report the results of recognition of online handwritten Tamil characters. We experimented with two different approaches. One is subspace based method wherein the interactions between the features in the feature spate are assumed to be linear. In the second approach, we investigated an elastic matching technique using dynamic programming principles. We compare the methods to find their suitability for an on-line form-filling application in writer dependent, independent and adaptive scenarios. The comparison is in terms of average recognition accuracy and the number of training samples required to obtain an acceptable performance. While the first criterion evaluates effective recognition capability of a scheme, the second one is important for studying the effectiveness of a scheme in real time applications. We also perform error analysis to determine the advisability of combining the classifiers.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Tappert, C.C., Suen, C.Y., Wakahara, T.: The state of the art in on-line handwriting recognition. IEEE Trans. Pattern Analysis and Machine Intelligence 12(8), 787–808 (1990)CrossRefGoogle Scholar
  2. 2.
    Sundaresan, C.S., Keerthi, S.S.: A study of representations for pen based handwriting recognition of Tamil characters. In: Fifth International Conference on Document Analysis and Recognition, September 1999, pp. 422–425 (1999)Google Scholar
  3. 3.
    Deepu, V.: On-line writer dependent handwriting character recognition, Master of Engineering project report, Indian Institute of Science, India (January 2003)Google Scholar
  4. 4.
    Keogh, E., Pazzani, M.: Derivative dynamic time warping. In: First SIAM International Conference on Data Mining (SDM 2001), Chicago, USA (2001)Google Scholar
  5. 5.
    Li, X., Yeung, D.Y.: On-line handwritten alphanumeric character recognition using dominant points in strokes. Pattern Recognition 30(1), 31–44 (1997)CrossRefGoogle Scholar
  6. 6.
    Joshi, N., Sita, G., Ramakrishnan, A.G., Madhvanath, S.: Comparison of elastic matching algorithms for on-line Tamil handwriting recognition. In: ICONIP 2004 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Niranjan Joshi
    • 1
  • G. Sita
    • 1
  • A. G. Ramakrishnan
    • 1
  • Sriganesh Madhvanath
    • 2
  1. 1.Dept. of Electrical Engg.Indian Institute of ScienceBangaloreIndia
  2. 2.Hewlett-Packard LaboratoriesBangaloreIndia

Personalised recommendations