Study on Printed Tibetan Character Recognition

  • Authors:
  • Ngo Drup;Dongcai Zhao;Puts Ren;Daluo Sanglangjie;Fang Liu;Bian Bawangdui

  • Affiliations:
  • -;-;-;-;-;-

  • Venue:
  • AICI '10 Proceedings of the 2010 International Conference on Artificial Intelligence and Computational Intelligence - Volume 01
  • Year:
  • 2010

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Abstract

Owing to special structure Tibetan characters, the recognition of traditional Tibetan characters encounters the problems of low recognition rates and poor recognition effects. Through conducting an in-depth study on features of the printed Tibetan characters, this paper develops a series of methods to increase recognition rate and improve the recognition effects of Tibetan characters even in the case of jamming. These methods are including local self-adaptive binary algorithm, segmentation based on the connected domain, grid-based fuzzy stroke feature extraction and so on. The results of the experiments indicate that the methods can definitely increase the recognition rates of the printed Tibetan character recognition system and improve its ability to prevent jamming.