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Script Identification for a Tri-lingual Document

  • Prakash K. Aithal
  • G. Rajesh
  • Dinesh U. Acharya
  • M. Krishnamoorthi
  • N. V. Subbareddy
Part of the Communications in Computer and Information Science book series (CCIS, volume 142)

Abstract

India is a multilingual multi-script country. States of India follow a three language formula. The document may be printed in English, Hindi and other state official language. For Optical Character Recognition (OCR) of such a multilingual document, it is necessary to identify the script before feeding the text lines to the OCRs of individual scripts. In this paper, a simple and efficient technique of script identification for Tamil, Hindi and English text lines from a printed document is presented. The proposed system uses horizontal projection profile to distinguish the three scripts. The feature extraction is done based on the horizontal projection profile of each text line. The knowledge base of the system is developed based on 20 different document images containing about 600 text lines. The proposed system is tested on 20 different document images containing about 200 text lines of each script and an overall classification rate of 100% is achieved.

Keywords

Multiscript Horizontal projection profile Rule based classifier 

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References

  1. 1.
    Pal, U., Choudhuri, B.B.: Script line separation from Indian multi-Script documents. In: Fifth International Conference on Document Analysis and Recognition, pp. 406–409. IEEE Computer Society Press, Los Alamitos (1999)Google Scholar
  2. 2.
    Pal, U., Sinha, S., Choudhuri, B.B.: Multi-Script line identification from Indian documents. In: Seventh International Conference on Document Analysis and Recognition, ICDAR, pp. 880–884 (2003)Google Scholar
  3. 3.
    Padma, M.C., Nagabhushan, P.: Identification and separation of text words of Kannada, Hindi and English languages through discriminating features. In: Second National Conference on Document Analysis and Recognition, Karnataka,India, pp. 252–260 (2003)Google Scholar
  4. 4.
    Choudhury, S., Harit, G., Madnani, S., Shet, R.B.: Identification of Scripts of Indian Languages by Combining Trainable Classifiers. In: ICVGIP, Bangalore, India (2000)Google Scholar
  5. 5.
    Tan, T.N.: Rotation Invariant Texture Features and their use in Automatic Script Identification. IEEE Trans. on Pattern Analysis and Machine Intelligence 20(7), 751–756 (1998)CrossRefGoogle Scholar
  6. 6.
    Chanda, S., Pal, U.: English, Devanagari and Urdu Text Identification. In: International conference on Document Analysis and Recognition, pp. 538–545 (2005)Google Scholar
  7. 7.
    Joshi, G.D., Garg, S., Sivaswamy, J.: Script Identification from Indian Documents. In: Bunke, H., Spitz, A.L. (eds.) DAS 2006. LNCS, vol. 3872, pp. 255–267. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Dhandra, B.V., Hangarge, M., Hegadi, R.: Word Level Script Identification in Bilingual Documents through Discriminating Features. In: IEEE - ICSCN 2007, Chennai, India, pp. 630–635 (2007)Google Scholar
  9. 9.
    Patil, B., SubbaReddy, N.V.: Neural network based system for script identification in Indian documents. In: Sadhana, India, vol. 27(part 1), pp. 83–97 (2002)Google Scholar
  10. 10.
    Zhou, L., Lu, Y., Tan, C.-L.: Bangla/English ScriptIdentification Based on Analysis of Connected Component Profiles. In: Bunke, H., Spitz, A.L. (eds.) DAS 2006. LNCS, vol. 3872, pp. 243–254. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Vijaya, P.A., Padma, M.C.: Text line identification from a multilingual document. In: International Conference on Document Image Processing (ICDIP-2009), Bangkok, pp. 302–305 (2009)Google Scholar
  12. 12.
    Ahmed Elgammal, M., Mohamed Ismail, A.: Techniques for language identification for hybrid Arabic-English document images. In: Sixth International Conference on Document Analysis and Recognition, Seattle, pp. 1100–1104 (2001)Google Scholar
  13. 13.
    Kasturi, R., Lawrence Gorman, O., Raju, V.G.: Document image analysis- a primer. In: Sadhana, India, vol. 27(part 1), pp. 3–22 (2002)Google Scholar
  14. 14.
    Dhanya, D., Ramakrishnan, A.G., Basapati, P.: Script Identification in printed bilingual documents. In: Sadhana, India, vol. 27(part 1), pp. 73–82 (2002)Google Scholar
  15. 15.
    Padma, M.C., Vijaya, P.A.: Identification and separation of Text words of Kannada, Telugu, Tamil, Hindi and English languages through visual discriminating features. In: International Conference on Advances in Computer Vision and Information Technology (ACVIT 2007), Aurangabad, India, pp. 1283–1291 (2007)Google Scholar
  16. 16.
    Prakash, Aithal, K., Rajesh, G., Dinesh Acharya, U., Krishnamoorthi, M., Subbareddy, N.V.: Text Line Script Identification for a Tri-lingual Document. In: International Conference on Computing Communication and Networking Technologies, Karur, India, pp. 1–3 (2010)Google Scholar
  17. 17.
    Padma, M.C., Vijaya, P.A.: Wavelet Packet Based Texture Features for Automatic Script Identification. International Journal of Image Processing 4(1) (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Prakash K. Aithal
    • 1
  • G. Rajesh
    • 1
  • Dinesh U. Acharya
    • 1
  • M. Krishnamoorthi
    • 1
  • N. V. Subbareddy
    • 1
  1. 1.Manipal Institute of TechnologyManipal UniversityManipalIndia

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