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Telugu Handwritten Isolated Characters Recognition using Two Dimensional Fast Fourier Transform and Support Vector Machine
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 116 - Number 5 |
| Year of Publication: 2015 |
| Authors: Raju Dara, Urmila Panduga |
10.5120/20330-0820
|
Raju Dara, Urmila Panduga . Telugu Handwritten Isolated Characters Recognition using Two Dimensional Fast Fourier Transform and Support Vector Machine. International Journal of Computer Applications. 116, 5 ( April 2015), 7-11. DOI=10.5120/20330-0820
Abstract
Research in character recognition is an old application in the area of pattern recognition and has attracted many researchers during the last few decades. Handwritten character recognition (HCR) is of two types namely, Online and Offline. The recognition accuracy for HCR is less than 60% as per the literature survey. Also the non existence of standard database for Indian languages is another reason for motivation of this work. This work describes Offline HCR by extracting features using 2D FFT and using the support vector machines for Telugu documents. The best percentage recognition accuracy for Telugu handwritten characters is 71%.
References
- P. N. Sastry and R. Krishnan. "Isolated Telugu palm leaf Character recognition using radon transforms–a novel approach". In IEEE-WICT, 2012.
- P. N. Sastry, R. Krishnan and T. V. Rajinikanth. Palm leaf Telugu character recognition using Hough transform. In Proceedings of International Conference on Advanced Computing Methodologies (ICACM-2011), pages 21–28, Dec 2011 Elsevier.
- P. N. Sastry, R. Krishnan and B. V. Sanker Ram. Telugu character recognition on palm leaves-a three dimensional approach technology. Spectrum (JNTU Hyderabad), 2(3):19–26, Nov. 2008.
- S. V. N. Manjunath Aradhya and G. Hemanth Kumar. Multilingual OCR system for south Indian scripts and English documents. In 5th IFIP International Conference on Intelligent Information Processing, pages 658–668, 2008 Elsevier.
- Munish Kumar, R. K. Sharma and M. K. Jindal. Offline Handwritten Gurumukhi Character Recognition: Study of Different Feature-Classifier Combinations. In the proceedings of the Workshop on Document Analysis and Recognition, Dec 2012.
- U. Bhattacharya and B. B. Chaudhuri. Handwritten numeral databases of Indian scripts and multistage recognition of mixed numerals. IEEE transactions on pattern analysis and machine intelligence, 31(3):444–457, Mar. 2009
- P. N. Sastry, R. Krishnan and B. V. Sanker Ram. Classification and identification of Telugu handwritten characters extracted from palm leaves using decision tree approach. ARPN Journal of Engineering and Applied Sciences, 5(3), Mar. 2010.
- Jawahar, C. V. , Pavan Kumar, M. N. S. S. K. , Ravi Kiran, S. S. , 2003. A bilingual OCR for Hindi-Telugu documents and its applications. In proceedings of ICDAR, 3-6 August, Edinburgh, pp 656-660.
- Prasad J. R. , Kulkarni U. V. , Prasad R. S. , "Offline handwritten character recognition of Gujarati script using pattern matching". ASID (Anti-counterfeiting, Security and Identification in Communication) 2009 pp. 611-615.
- Sutha, J. and Ramaraj N. , "Neural Network Based Offline Tamil handwritten character recognition system". International conference on computational Intelligence and Multimedia Applications", 2007, vol. 2, pp. 446-550.
- R. Jagadeesh Kannan and R. Prabhakar, "An improved Handwritten Tamil Character Recognition System using Octal Graph", Journal of computer science, vol. 4, No. 7, 2008, pp. 509-516.
- Kandan Ramakrishnan, Arvind K. R. and A. G. Ramakrishnan, "Localization of handwritten text in documents using moment invariants and Delaunay Triangulation", International Conference on computational Intelligence and Multimedia Applications, vol. 3 2007, pp. 408-414.
- Arun K. Pujari, C. Dhanunjaya Naidu, M. Sreenivasa Rao and B. C. Jinaga, "An intelligent character recognizer for Telugu scripts using multiresolution analysis and associative memory", Image and vision computing, vol. 22. 2004, pp. 1221-1227.
- H. Bunke, M. Roth and E. G. Schukat-Talamazzini, "Offline Cursive Handwriting Recognition using Hidden Markov Models", Pattern Recognition, Vol. 28, No. 9, 1995, pp. 1339-1413.
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