Multi-font Telugu Text Recognition Using Hidden Markov Models and Akshara Bi-grams

  • Koteswara Rao DevarapalliEmail author
  • Atul Negi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10481)


Recent advances in the information technology made possible to introduce many Unicode Telugu fonts for the documentation needs of present society. But the recognition of documents printed in a variety of fonts poses new challenges in building Telugu OCR systems. In this paper, we demonstrate multi-font Telugu printed word recognition using implicit segmentation approach that provides segmentation as a by-product of recognition. Our word recognition approach relies on Hidden Markov Models and akshara bi-gram language model to recognize word images in terms of aksharas (characters). The training set of word images is prepared from document images of popular books and the synthetic document images generated using 8 different Unicode fonts. The testing involves matching the feature vector sequence against sequence of akshara HMMs based on bi-grams. The CER and WER of this system are 21% and 37% respectively. The performance of our system is very encouraging.


Akshara Bi-gram DCT HMM Telugu OCR Word recognition 


  1. 1.
    Bazzi, I., Schwartz, R., Makhoul, J.: An omnifont open-vocabulary OCR system for English and Arabic. IEEE Trans. Pattern Anal. Mach. Intell. 21(6), 495–504 (1999)CrossRefGoogle Scholar
  2. 2.
    Elms, A., Procter, S., Illingworth, J.: The advantage of using an HMM-based approach for faxed word recognition. Int. J. Doc. Anal. Recogn. 1(1), 18–36 (1998)CrossRefGoogle Scholar
  3. 3.
    Khorsheed, M.S.: Offline recognition of omnifont Arabic text using the HMM toolkit (HTK). Pattern Recogn. Lett. 28(12), 1563–1571 (2007)CrossRefGoogle Scholar
  4. 4.
    Krishnan, P., Sankaran, N., Singh, A.K., Jawahar, C.V.: Towards a robust OCR system for Indic scripts. In: 2014 11th IAPR International Workshop on Document Analysis Systems (DAS), pp. 141–145, April 2014Google Scholar
  5. 5.
    Kumar, P.P., Bhagvati, C., Negi, A., Agarwal, A., Deekshatulu, B.L.: Towards improving the accuracy of Telugu OCR systems. In: ICDAR, pp. 910–914. IEEE Computer Society (2011)Google Scholar
  6. 6.
    Lam, L., Lee, S.-W., Suen, C.: Thinning methodologies-a comprehensive survey. IEEE Trans. Pattern Anal. Mach. Intell. 14(9), 869–885 (1992)CrossRefGoogle Scholar
  7. 7.
    Natarajan, P., Lu, Z., Schwartz, R., Bazzi, I., Makhoul, J.: Multilingual machine printed OCR. Int. J. Pattern Recogn. Artif. Intell. 15(01), 43–63 (2001)CrossRefGoogle Scholar
  8. 8.
    Natarajan, P., MacRostie, E., Decerbo, M.: The BBN byblos Hindi OCR system. In: Govindaraju, V., Setlur, S. (eds.) Guide to OCR for Indic Scripts. Advances in pattern recognition, pp. 173–180. Springer, London (2010). doi: 10.1007/978-1-84800-330-9_9 Google Scholar
  9. 9.
    Negi, A., Bhagvati, C., Krishna, B.: An OCR system for Telugu. In: ICDAR, pp. 1110–1114. IEEE Computer Society (2001)Google Scholar
  10. 10.
    Rabiner, L.: A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77(2), 257–286 (1989)CrossRefGoogle Scholar
  11. 11.
    Rasagna, V., Jinesh, K.J., Jawahar, C.V.: On multifont character classification in Telugu. In: Singh, C., Singh Lehal, G., Sengupta, J., Sharma, D.V., Goyal, V. (eds.) ICISIL 2011. CCIS, vol. 139, pp. 86–91. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-19403-0_14 CrossRefGoogle Scholar
  12. 12.
    Roy, P., Roy, S., Pal, U.: Multi-oriented text recognition in graphical documents using HMM. In: 2014 11th IAPR International Workshop on Document Analysis Systems (DAS), pp. 136–140, April 2014Google Scholar
  13. 13.
    Vasantha Lakshmi, C., Patvardhan, C.: A multi-font OCR system for printed Telugu text. In: 2002 Proceedings of Language Engineering Conference, pp. 7–17, December 2002Google Scholar
  14. 14.
    Wu, Y., Shivakumara, P., Wei, W., Lu, T., Pal, U.: A new ring radius transform-based thinning method for multi-oriented video characters. IJDAR 18(2), 137–151 (2015)CrossRefGoogle Scholar
  15. 15.
    Young, S., Evermann, G., Gales, M., Hain, T., Kershaw, D., Liu, X.A., Moore, G., Odell, J., Ollason, D., Povey, D., Valtchev, V., Woodland, P.: The HTK Book (for HTK Version 3.4). Cambridge University Engineering Department (2006)Google Scholar

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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringMahatma Gandhi Institute of TechnologyHyderabadIndia
  2. 2.School of Computer and Information SciencesUniversity of HyderabadGachibowli, HyderabadIndia

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