Skip to main content
Springer Nature Link
Log in

A novel SVM-based handwritten Tamil character recognition system

  • THEORETICAL ADVANCES
  • Published:
Pattern Analysis and Applications Aims and scope Submit manuscript

Abstract

This paper describes a system for recognizing offline handwritten Tamil characters using support vector machine (SVM). Data samples are collected from different writers on A4 sized documents. They are scanned using a flat bed scanner at a resolution of 300 dpi and stored as gray-scale images. Various preprocessing operations are performed on the digitized image to enhance the quality of the image. Pixel densities are calculated for 64 different zones of the image and these values are used as the features of a character. These features are used to train the SVM. The SVM is tested for the first time to recognize handwritten Tamil characters. The system has achieved a very good recognition accuracy of 82.04% on the handwritten Tamil character database.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Pal U, Chaudhuri BB (2004) Indian script character recognition: a survey. Pattern Recognit 37:1887–1899

    Article  Google Scholar 

  2. Mantas J (1986) An overview of character recognition methodologies. Pattern Recognit 19(6):425–430

    Article  Google Scholar 

  3. Govindan VK, Shivaprasad AP (1990) Character recognition—a review. Pattern Recognit 23(7):671–683

    Article  Google Scholar 

  4. Srihari SN, Yang X, Ball GR (2007) Offline Chinese handwriting recognition: an assessment of current technology. Front Comput Sci China 1(2):137–155

    Article  Google Scholar 

  5. Lorigo LM, Govindaraju V (2006) Offline Arabic handwriting recognition: a survey. IEEE Trans Pattern Anal Mach Intell 28(5):712–724

    Article  Google Scholar 

  6. Gatos B, Ntzios K, Pratikakis I, Petridis S, Konidaris T, Perantonis SJ (2006) An efficient segmentation-free approach to assist old Greek handwritten manuscript OCR. Pattern Anal Appl 8:305–320

    Article  MathSciNet  Google Scholar 

  7. Jaeger S, Nakagawa M, Liu C-L (2002) A brief survey on the state of the art in on-line handwriting recognition for Japanese and western script. Tech Rep IEICE 101(713):1–8

    Google Scholar 

  8. Vasantha Lakshmi C, Patvardhan C (2004) An optical character recognition system for printed Telugu text. Pattern Anal Appl 7:190–204

    Google Scholar 

  9. Siromoney G, Chandrasekaran R, Chandrasekaran M (1978) Computer recognition of printed Tamil character. Pattern Recognit 10:243–247

    Article  MATH  Google Scholar 

  10. Chinnuswamy P, Krishnamoorthy SG (1980) Recognition of hand printed Tamil characters. Pattern Recognit 12:141–152

    Article  Google Scholar 

  11. Suresh RM, Ganesan L (1999) Recognition of hand printed Tamil characters using classification approach. ICAPRDT, Kolkata, pp 63–84

    Google Scholar 

  12. Hewavitharana S, Fernando HC (2002) A two stage classification approach to Tamil handwriting recognition. In: Tamil Internet 2002, California, USA, pp 118–124

  13. Bhattacharya U, Ghosh SK, Parui SK (2007) A two stage recognition scheme for handwritten Tamil characters. In: Proceedings of the ninth international conference on document analysis and recognition (ICDAR 2007). IEEE Computer Society, Washington, DC, pp 511–515

    Google Scholar 

  14. Sutha J, Ramaraj N (2007) Neural network based offline Tamil handwritten character recognition system. In: Proceedings of the international conference on computational intelligence and multimedia applications, vol 2. IEEE Computer Society, Washington, DC, pp 446–450

    Google Scholar 

  15. Shanthi N, Duraiswamy K (2005) Preprocessing algorithms for the recognition of Tamil handwritten characters. In: Third international CALIBER 2005, Kochi, pp 77–82

  16. Casey RG, Lecolinet E (1996) A survey of methods and strategies in character segmentation. IEEE Trans Pattern Anal Mach Intell 18(7):690–706

    Article  Google Scholar 

  17. Plamondon R, Srihari SN (2000) On-line and off-line handwriting recognition: a comprehensive survey. IEEE Trans Pattern Anal Mach Intell 22(1):63–84

    Article  Google Scholar 

  18. Otsu N (1979) A threshold selection method from grey level histogram. IEEE Trans Syst Man Cybern 9(1):62–66

    Article  MathSciNet  Google Scholar 

  19. Lam L, Lee S-W, Suen CY (1992) Thinning methodologies—a comprehensive survey. IEEE Trans Pattern Anal Mach Intell 14(9):869–885

    Article  Google Scholar 

  20. Trier ØD, Jain AK, Taxt T (1996) Feature extraction methods for character recognition—a survey. Pattern Recognit 29(4):641–662

    Article  Google Scholar 

  21. Boser BE, Guyon IM, Vapnik VN (1992) A training algorithm for optimal margin classifiers. In: Proceedings of the fifth annual workshop on computational learning theory, July 27–29, ACM, New York

  22. Christopher Burges JC (1998) A tutorial on support vector machines for pattern recognition. Data Min Knowl Discov 2(2):21–67

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Technology, K.S. Rangasamy College of Technology, Tiruchengode, India

    N. Shanthi

  2. K.S. Rangasamy College of Technology, Tiruchengode, India

    K. Duraiswamy

Authors
  1. N. Shanthi
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. K. Duraiswamy
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to N. Shanthi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Shanthi, N., Duraiswamy, K. A novel SVM-based handwritten Tamil character recognition system. Pattern Anal Applic 13, 173–180 (2010). https://doi.org/10.1007/s10044-009-0147-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10044-009-0147-0

Keywords