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Handbook of Document Image Processing and Recognition pp 459–486Cite as

Asian Character Recognition

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Abstract

This chapter deals with the automated recognition of Asian scripts and focuses primarily on text belonging to two script families, viz., oriental scripts such as Chinese, Japanese, and Korean (CJK) and scripts from the Indian subcontinent (Indic) such as Devanagari, Bangla, and the scripts of South India. Since these scripts have attracted the greatest interest from the document analysis community and cover most of the issues potentially encountered in the recognition of Asian scripts, application to other Asian scripts should primarily be a matter of implementation. Specific challenges encountered in the OCR of CJK and Indic scripts are due to the large number of character classes and the resultant high probability of confusions between similar character shapes for a machine reading system. This has led to a greater role being played by language models and other post-processing techniques in the development of successful OCR systems for Asian scripts.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, University at Buffalo, The State University of New York, 113 Davis Hall, 14260-2500, Buffalo, NY, USA

    Srirangaraj Setlur

  2. Department of Computer Science and Engineering, University at Buffalo, The State University of New York, 113 Davis Hall, 14260-2500, Buffalo, NY, USA

    Zhixin Shi

Authors
  1. Srirangaraj Setlur
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  2. Zhixin Shi
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Corresponding author

Correspondence to Srirangaraj Setlur .

Editor information

Editors and Affiliations

  1. University of Maryland, College Park, MD, USA

    David Doermann

  2. Université de Lorraine, Nancy, France

    Karl Tombre

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© 2014 Springer-Verlag London

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Setlur, S., Shi, Z. (2014). Asian Character Recognition. In: Doermann, D., Tombre, K. (eds) Handbook of Document Image Processing and Recognition. Springer, London. https://doi.org/10.1007/978-0-85729-859-1_14

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