Abstract
Optical Character Recognition (OCR) systems have been effectively developed for the recognition of printed characters of non-Indian languages. Efforts are on the way for the development of efficient OCR systems for Indian languages, especially for Kannada, a popular South Indian language. We present in this paper an OCR system developed for the recognition of basic characters (vowels and consonants) in printed Kannada text, which can handle different font sizes and font types. Hu’s invariant moments and Zernike moments that have been progressively used in pattern recognition are used in our system to extract the features of printed Kannada characters. Neural classifiers have been effectively used for the classification of characters based on moment features. An encouraging recognition rate of 96.8% has been obtained. The system methodology can be extended for the recognition of other south Indian languages, especially for Telugu.
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References
Ashwin T V, Sastry P S 2002 A font and size-independent OCR system for printed Kannada documents using support vector machines. Sādhanā 27: 35–58
Chong Chee-Way, Raveendran P, Mukundan R 2003 A comparative analysis of algorithms for fast computation of Zernike moments. Pattern Rec. 36: 731–742
Girosi F, Poggio T 1990 Networks and the best approximation property. Bio. Cybernetics. 63: 169–176
Gonzalez R C, Woods R E 1993 Digital image processing (Boston, MA, USA: Addison Wesley Longman Publishing Co. Inc.)
Hu M-K 1962 Visual pattern recognition by moment invariants. IRE Trans. Inf. Theory. IT-8: 179–187
Jawahar C V, Pavan Kumar, Ravi Kiran S S 2003 A Bilingual OCR for Hindi-Telugu documents and its applications. Proc. Seventh Int. Confer. on Document Anal. and Rec. 408–412
Khotanzad A 1998 Rotation invariant pattern recognition using Zernike moments. Proc. Int. Conf. on Pattern Rec. 326–328
Kunte Sanjeev R, Sudhaker Samuel R D 2006 A two-stage character segmentation scheme for Printed Kannada text. J. Graphics, Vision and Image Processing 6: 1–8
Moody J, Darken C J 1989 Fast learning in network of locally-tuned processing units. J. Neural Comput. 1: 281–294
Mukundan R, Ong S H, Lee P A 2001 Image analysis by Tchebichef moments. IEEE Trans. Image Processing 10: 1357–1364
Mohammed Al-Rawi, Yang Jie 2002 Practical fast computation of Zernike moments. J. Comput. Sci. and Technol. 17: 181–188
Nagabhushan P, Pai Radhika M 1999 Modified region decomposition method and optimal depth decision tree in the recognition of non-uniform sized characters — An experimentation with Kannada characters. Pattern Rec. Lett. 20: 1467–1475
Negi Atul, Chakravarthy Bhagavathi, Krishna B 2001 An OCR system for Telugu. Proc. Sixth Inter. Confer. on Document Anal. and Rec. 1110–1114
Park J, Wsandberg J 1991 Universal approximation using radial basis function neural networks. J. Neural Comput. 1: 246–257
Teague M R 1980 Image analysis via the general theory of moments. J. Optical Soc. Amer. 70: 920–930
VijayaKumar B, Ramakrishnan A G 2004 Radial basis function and sub-space approach for printed Kannada text recognition. Proc. IEEE ICASSP 2004 5: 321–324
Zernike F 1934 Physica. 1: 689–704
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Sanjeev Kunte, R., Sudhaker Samuel, R.D. A simple and efficient optical character recognition system for basic symbols in printed Kannada text. Sadhana 32, 521–533 (2007). https://doi.org/10.1007/s12046-007-0039-1
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DOI: https://doi.org/10.1007/s12046-007-0039-1