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A Recognition System for Online Handwritten Tibetan Characters

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Book cover Graphics Recognition. New Trends and Challenges (GREC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7423))

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Abstract

This paper describes a recognition system for online handwritten Tibetan characters using advanced techniques in character recognition. To eliminate noise points of handwriting trajectories, we introduce a de-noising approach by using dilation, erosion, thinning operators of the mathematical morphology. Selecting appropriate structuring elements, we can clear up large amounts of noises in the glyphs of the character. To enhance the recognition performance, we adopt three-stage classification strategy, where the top rank output classes by the baseline classifier are re-classified by similar character discrimination classifier. Experiments have been carried out on two databases MRG-OHTC and IIP-OHTC. Test results show the used recognition algorithm is effective and can be applied in pen-based mobile devices.

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Author information

Authors and Affiliations

  1. National Engineering Research Center of Fundamental Software, Institute of Software, Chinese Academy of Sciences, Beijing, P.R. China

    Long-Long Ma & Jian Wu

Authors
  1. Long-Long Ma
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  2. Jian Wu
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Chung-Ang University, 221 Heuksukdong, 156-756, Dongjakku, Seoul, Korea

    Young-Bin Kwon

  2. Laboratoire L3i, Université de La Rochelle, Avenue Michel Crépeau, 17042, La Rochelle Cedex 1, France

    Jean-Marc Ogier

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Ma, LL., Wu, J. (2013). A Recognition System for Online Handwritten Tibetan Characters. In: Kwon, YB., Ogier, JM. (eds) Graphics Recognition. New Trends and Challenges. GREC 2011. Lecture Notes in Computer Science, vol 7423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36824-0_10

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  • DOI: https://doi.org/10.1007/978-3-642-36824-0_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36823-3

  • Online ISBN: 978-3-642-36824-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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