Call for Paper - April 2021 Edition
IJCA solicits original research papers for the April 2021 Edition. Last date of manuscript submission is March 22, 2021. Read More

Handwritten Kannada Characters Recognition using Curvelet Transform

IJCA Proceedings on National conference on Digital Image and Signal Processing
© 2015 by IJCA Journal
DISP 2015 - Number 3
Year of Publication: 2015
Shashikala Parameshwarppa
B. V. Dhandra

Shashikala Parameshwarppa and B v Dhandra. Article: Handwritten Kannada Characters Recognition using Curvelet Transform. IJCA Proceedings on National conference on Digital Image and Signal Processing DISP 2015(3):12-16, April 2015. Full text available. BibTeX

	author = {Shashikala Parameshwarppa and B.v. Dhandra},
	title = {Article: Handwritten Kannada Characters Recognition using Curvelet Transform},
	journal = {IJCA Proceedings on National conference on Digital Image and Signal Processing},
	year = {2015},
	volume = {DISP 2015},
	number = {3},
	pages = {12-16},
	month = {April},
	note = {Full text available}


The Selection of a feature extraction method for recognition of an object/character is probably the single most factors in achieving high recognition accuracy. Therefore, in this paper an effort is made to identify the Second Generation Discrete Curvelet Transform (DCTG2) as the potential features for recognition of handwritten Kannada character system . Images are made noise free by median filter and images are normalized into 64x64 pixels. Curvelet transform with different scales are applied to the input images to generate the curvelet coefficients . Then the standard deviation are computed for the curvelet coefficients to form feature vector of size 20. The total of 2800 Kannada vowels and 6800 handwritten Kannada consonants of sample images are used for classification based on the KNN classifier. To test the performance of the proposed algorithm two fold cross validation is used. The average recognition accuracy of 90. 57% is obtained for handwritten basic Kannada characters respectively. The proposed algorithm is independent of thinning and skew of the character images.


  • Oivind Trier, Anil Jain, Torfinn Taxt (1996) Pattern Recognition, Vol 29, No 4, pp 641-662.
  • R. O. Duda, P. E. Hart, D. G. Stork, Pattern Classification, 2nd ed. , Wiley-New York.
  • R. M. K. Sinha, Scott D. Conell and Anil K. Jain, "Recognition of Unconstrained Online Devanagari Characters", Proceedings of the 15th International Conference on Pattern Recognition, Barcelona, Sept. 2000. pp. 368-371.
  • Aradhya M. , Niranjana S. K. , Hemantha kumar G. , (2010) "Probabilistic Neural Network based Approach for Handwritten Character Recognition" Special Issue of IJCCT, Vol. 1 Issue 2,3,4 pp. 9-13
  • B. V. Dhandra, Mallikarjun Hangarge and Gururaj Mukarambi (2012). "A Zone Based Character Recognition Engine for Kannada and English Scripts". Elsevier Science Direct, pp. 3292-3299.
  • Kunte Sanjeev R. , Sudhaker Samuel (2006). "A simple and efficient optical character recognition system for basic symbols in printed Kannada text". Sadhana, Vol. 32, Part 5, pp. 521-533.
  • B. V. Dhandra, Mallikarjun Hangarge, Vijayalaxmi M. B. and Gururaj Mukarambi (2014). "Script Identification Using Discrete Curvelet Transfirms". IJCA, Recent Advances in Information Technology. pp. 16-20
  • E. Cand`es, L. Demanet, D. Donoho and L. Ying, "Fast Discrete Curvelet Transforms," Technical Report, July 2005, pp. 761-799
  • B. V. Dhandra, Mallikarjun Hangarge and Shashikala Parameshwarappa (2010). "Multi-Font Kannada Vowels and Numerals Recognition Based on Modified Invariant Moments", IJCA, Special Issue on RTIPPR (3): pp 146–151.
  • G. G. Rajput, Rajeswari Horakeri (2013). "Unconstrained Kannada Handwritten Character Recognition Using Multi-level SVM Classifier", P. Maji et al. (Eds): PREMI 2013, LNCS 8251, pp. 204-212
  • Dinesh Acharya U. , N. V. Subba Reddy and Krishnamoorthi (2008). Hierarchical Recognition System for Machine Printed Kannada Characters. IJCSNS LNCS International Journal of Computer Science and Network Security Vol. 8 No. 11, pp. 44-53.
  • Nagbhushan P. , Pai Radhika M. (1999). Modified region decomposition method and optimal depth decomposition tree in the recognition of non –uniform sized characters – An experimentation with Kannada characters. Pattern Recognition. Letter. 20: pp. 1467-1475
  • E. J. Cand`es and D. L. Donoho, "Curvelets–A Surprisingly Effective Non adaptive Representation for Objects with Edges," in Curves and Surfaces, C. Rabut, A. Cohen, and L. L. Schumaker, Ed. , Vanderbilt University Press, Nashville, TN, 2000, pp. 105–120.
  • Ashwin T. V. , Sastry P. S. (2002). A Fonts and Size-Independent OCR System for Printed Kannada Documents Using Support Vector Machines. Sadhana, 27: pp. 35-58.
  • J. L. Starck, E. J. Cand`es, and D. L. Donoho (2002). "The Curvelet Transform for Image Denoising", IEEE Trans. Im. Proc. , Vol. 11, No. 6, pp. 670-684
  • Gonzales R. C. and Woods, R. E. (2002). Digital Image Processing 2nd Ed. Upper Saddle River, N. J. : Prentice- Hall, Inc. pp. 261-269
  • E. J. Candès, L. Demanet, D. L. Donoho, L. Ying. (2003) "Fast Discrete Curvelet Transforms". Multiscale Model. Simul. , pp. 861-899.
  • Nagabhushan P. , Angadi S. A. , Anami B. S. (2003). A Fuzzy Statistical Approach to Kannada Vowel Recognition based on Invariant Moments, Proceedings of NCDAR -2003, PESCE, Mandya, pp. 275-285.
  • U. Pal, B. B. Chaudhuri (2004). Indian Script Character Recognition: A Survey. Pattern Recognition, 37 (2004), pp. 1887–1899.
  • R. Sanjeev Kunte, R. D. Sudhaker Samuel (2007). An OCR System for Printed Kannada Text Using Two-stage Multi-network Classification Approach Employing Wavelet Features, International Conference on Computational Intelligence and Multimedia Applications, pp. 349-355.
  • M. J. Fadili and J. L. Starck (2007). Curvelets and Ridgelets, "Encyclopedia of Complexity and System Science", pp. 1-29
  • Karthik Sheshadri, Pavan Kumar, T. Ambekar, Deeksha Padma Prasad and Dr. Ramakanth P. Kumar (2010). An OCR System for Printed Kannada using K-Means Clustering. IEEE International Conference on Industrial Technology (ICIT), pp. 183-187.
  • Srikanta Murthy, Mamata H. R. , Sucharita S. , "Multi –font and Multi-size Kannada Character Recognition based on the Curvelet and Standard Deviation", IJCA, Vol 35, December 2011. pp. 101-104
  • Rampalli R. , Ramakrishan, Anagari G. (2011). Fusion of Complementary Online and Offline Strategies for Recognition of Handwritten Kannada Characters, Journal of Universal Computer Science, 17(1): pp. 81-93.