Skip to main content
SpringerLink
Log in

Online Character Recognition in Multi-lingual Framework

  • Conference paper
  • First Online:
Intelligent Systems Technologies and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 384))

  • 1425 Accesses

Abstract

Online character recognition research area becomes very prominent due to widespread popularity of handheld devices. Common people like to interact with each other on their own native language through their handheld device. Multi-lingual country like India requires a common framework to incorporate all languages. Here we propose a unified approach to recognize characters in the different languages in a single multi-lingual framework. Stroke rule generation is the first step in the character recognition. Statistical stroke model approach in which probabilities from stroke rule along with confidence measurement obtained from the PSFAM (Probabilistic Simplified Fuzzy ARTMAP) classifier is used for recognizing character. We had tested with Hindi, Malayalam, Tamil and Urdu. Accuracy varies from 85-95% for different languages depending on the number of training samples used.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Swethalakshmi, H., Jayaram, A., Chakraborty, V.S., Sekhar, C.C.: Online handwritten character recognition of devanagari and telugu characters using support vector machines. In: Proc. 10th IWFHR, pp. 367−372

    Google Scholar 

  2. Bharath, A., Madhvanath, S.: HMM-Based Lexicon-Driven and Lexicon-Free Word Recognition for Online Handwritten Indic Scripts. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(4) (2012)

    Google Scholar 

  3. Kubatur, S., Sid-Ahmed, M., Ahmadi, M.: A neural network approach to online devanagari handwritten character recognition. In: International Conference on High Performance Computing and Simulation (HPCS) (2012)

    Google Scholar 

  4. Sundaram, S., Ramakrishnan, A.G.: Two dimensional principal component analysis for online tamil character recognition. In: Proc. 11th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 88−93 (2008)

    Google Scholar 

  5. Kunwar, R., Ramakrishnan, A.G.: Online handwriting recognition of tamil script using fractal geometry. In: International Conference on Document Analysis and Recognition (ICDAR) (2011)

    Google Scholar 

  6. Primekumar, K.P., Idiculla, S.M.: On-line malayalam handwritten character recognition using wavelet transform and SFAM. In: 3rd International Conference on Electronics Computer Technology (ICECT) (2011)

    Google Scholar 

  7. Sampath, A., Tripti, C., Govindaru, V.: Freeman Code Based Online Handwritten Character Recognition For Malayalam Using Back propagation Neural Networks. Advanced Computing: an International Journal (ACIJ) 3(4) (2012)

    Google Scholar 

  8. Husain, S.A., Sajjad, A., Anwar, F.: Online urdu character recognition system. In: IAPR Conference on Machine Vision Applications (2007)

    Google Scholar 

  9. Ullah Khan, K., Haider, I.: Online recognition of multi-stroke handwritten urdu characters. In: International Conference on Image Analysis and Signal Processing (IASP) (2010)

    Google Scholar 

  10. Jaeger, S., et al.: Online handwriting recognition: the NPen ++ recognizer. International Journal on Document Analysis and Recognition (IJDAR) 3(3), 169–180 (2001)

    Article  Google Scholar 

  11. Vidya, V., Indhu, T.R., Bhadran, V.K.: Reordering of delayed strokes for online hindi word recognition. In: International Conference on Contemporary Computing and Informatics (IC3I) (2014)

    Google Scholar 

  12. Carpenter, G.A., et al.: Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps. IEEE Transaction on Neural Networks 3(5) (1992)

    Google Scholar 

  13. Vakil-Baghmisheh, M.-T., Paves, N.: A Fast Simplified Fuzzy ARTMAP Network. Neural Processing Letters 17(3), 273–316 (2003)

    Article  Google Scholar 

  14. Keyarsalan, M., Montazer, G.H.A., Kazemi, K.: Font-based persian character recognition using simplified fuzzy ARTMAP neural network improved by fuzzy sets and particle swarm optimization. In: IEEE Congress on Evolutionary Computation (2009)

    Google Scholar 

  15. Lim, C.P., Harrison, R.F.: Probabilistic fuzzy artmap : an autonomous neural network architecture for bayesian probability estimation. In: Fourth International Conference on Artificial Neural Networks (1995)

    Google Scholar 

  16. Jervis, B.W., Garcia, T., Giahnakis, E.P.: Probabilistic simplified fuzzy ARTMAP (PSFAM). In: IEE Proceeding on Science Measurement and Technology, vol. 146(4) (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Development and Advance Computing, Trivandrum, Kerala, India

    V. Vidya, T. R. Indhu & V. K. Bhadran

Authors
  1. V. Vidya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. R. Indhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. K. Bhadran
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. Vidya .

Editor information

Editors and Affiliations

  1. Dipartimento di Ingegneria dell’ Informazione (DINFO) , Universita degli Studi di Firenze, Firenze, Italy

    Stefano Berretti

  2. School of CS/IT, Indian Institute of Information Tech. and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  3. Indian Institute of Management Rohtak, Rohtak, Haryana, India

    Praveen Ranjan Srivastava

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Vidya, V., Indhu, T.R., Bhadran, V.K. (2016). Online Character Recognition in Multi-lingual Framework. In: Berretti, S., Thampi, S., Srivastava, P. (eds) Intelligent Systems Technologies and Applications. Advances in Intelligent Systems and Computing, vol 384. Springer, Cham. https://doi.org/10.1007/978-3-319-23036-8_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-23036-8_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23035-1

  • Online ISBN: 978-3-319-23036-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation