Research Article | OPEN ACCESS
Recognition of South Indian Language Numerals Using Minimum Distance Classifier
F. Jennifer Alin and K.N. Saravanan
Department of Computer Science, Christ University, Bangalore, 560029, India
Research Journal of Applied Sciences, Engineering and Technology 2017 4:161-169
Received: February 3, 2017 | Accepted: March 19,2017 | Published: April 15, 2017
Abstract
The recognition of handwritten and machine printed numerals have received extensive attention in pattern recognition. Indian handwritten character identification is slightly demanding because of the presence of character modifiers and also many documents consists of numerals which are both printed and handwritten. There are plenty of recognition systems developed for numeral recognition. Our aim is to develop a single framework or recognition system which could distinguish between numerals of various languages. Mixture of printed and handwritten character numerals in Indian context normally show up in documents such as application forms, postal mail, office letters and so forth. Generally, Humans can distinguish the difference in characters but to make a machine understand is challenging. Hence in order to make the machine understand numerals of different languages, this study has been carried out. The recognition rate of 87.96, 87.93, 86.93 and 89.16%, respectively has been achieved for Kannada, Telugu, Tamil and Malayalam numerals respectively.
Keywords:
Character modifiers, handwritten character, pattern recognition, postal mail, solitary document,
References
-
Candès, E., L. Demanet, D. Donoho and L. Ying, 2006. Fast discrete curvelet transforms. Multiscale Model. Sim., 5(3): 861-899.
CrossRef
- Elnagar, A., F. Al-Kharousi and S. Harous, 1997. Recognition of handwritten Hindi numerals using structural descriptors. Proceeding of the IEEE International Conference on Systems, Man and Cybernetics, Computational Cybernetics and Simulation. Orlando, FL, 2: 983 988.
CrossRef
- Majhi, B., J. Satpathy and M. Rout, 2011. Efficient recognition of odiya numerals using low complexity neural classifier. Proceeding of the International Conference on Energy, Automation and Signal (ICEAS, 2011), pp: 140-143.
CrossRef
- Mozaffari, S., K. Faez and M. Ziaratban, 2005. Structural decomposition and statistical description of Farsi/Arabic handwritten numeric characters. Proceeding of the 8th International Conference on Document Analysis and Recognition, 1: 237-241.
CrossRef
-
Pal, U. and B.B. Chaudhuri, 2004. Indian script character recognition: A survey. Pattern Recogn., 37(9): 1887-1899.
CrossRef
-
Purkait, P. and B. Chanda, 2010. Off-line recognition of hand-written Bengali numerals using morphological features. Proceeding of the 12th International Conference on Frontiers in Handwriting Recognition. Kolkata, India, pp: 363-368.
CrossRef
-
Sanossian, H., 1998. Feature extraction technique for Hindi numerals. Proceeding of the IEEE Signal Processing Society Workshop Neural Networks for Signal Processing VIII. Cambridge, pp: 524-530.
CrossRef
- Chaudhuri, B.B. and U. Pal, 1998. A complete printed bangla OCR system. Pattern Recogn., 31(5): 531-549.
CrossRef
-
Dhandra, B.V., M. Hangarge and G. Mukarambi, 2010. Spatial features for handwritten Kannada and English character recognition. Int. J. Comput. Appl., Special Issue on RTIPPR-2010, 3: 146-151.
Direct Link
- Dinesh Acharya, U., N.V. Subba Reddy and Krishnamoorthi, 2007. Isolated handwritten Kannada numeral recognition using structural feature and K-means cluster. Proceeding of the IISN, pp: 125-129.
-
Hanmandlu, M., A.V. Nath, A.C. Mishra and V.K. Madasu, 2007. Fuzzy model based recognition of handwritten Hindi numerals using bacterial foraging. Proceeding of the 6th IEEE/ACIS International Conference on Computer and Information Science. Melbourne, Australia.
CrossRef
-
Hossain, M.Z., M.A. Amin and H. Yan, 2011. Rapid feature extraction for Bangla handwritten digit recognition. Proceeding of the International Conference on Machine Learning and Cybernatics (ICMLC, 2011). Guilin, 4:1832-1837.
CrossRef
- Impedovo, S., R. Modugno and G. Pirlo, 2006. A feedback-based framework for continuous evaluation of e-learning acticities. Proceeding of the 3rd WSEAS/IASME International Conference on Engineering Education. Vouliagmeni, Greece, pp: 258-262.
Direct Link
- Nagabhushan, P. and R.M. Pai, 1999. Modified region decomposition method and optimal depth decision tree in the recognition of non-uniform sized characters – An experimentation with Kannada characters. Pattern Recogn. Lett., 20(14): 1467-1475.
CrossRef
- Nagabhushan, P., S.A. Angadi, and B.S. Anami, 2003. A fuzzy statistical approach to kannada vowel recognition based on invariant moments. Proceeding of the 2nd National Conference on Document Analysis and Recognition (NCDAR), pp: 275-285.
-
Rahiman, M.A. and M.S. Rajasree, 2009. A detailed study and analysis of OCR research in south Indian scripts. Proceeding of the International Conference on Advances in Recent Technologies in Communication and Computing (ARTCom'09), pp: 31-38.
CrossRef
-
Rajashekararadhya, S.V. and P. Vanaja Ranjan, 2008. Neural network based handwritten numeral recognition of Kannada and Telugu scripts. Proceeding of the IEEE Region 10 Conference on TENCON 2008-2008, pp: 1-5.
CrossRef
- Rajput, G.G. and S.M. Mali, 2010. Fourier descriptor based isolated Marathi Handwritten numeral recognition. Int. J. Comput. Appl., 3(4): 9-13.
CrossRef
- Sanjeev Kunte, R. and R.D. Sudhaker Samuel, 2007. A simple and efficient optical character recognition system for basic symbols in printed Kannada text. Sadhana, 32(5): 521-533.
CrossRef
- Saravanan, K.N. and R. Anitha, 2016. Recognition of multi-lingual handwritten numerals using partial derivatives. Res. J. Appl. Sci. Eng. Technol., 12(1): 27-36.
CrossRef
- Sharma, N., U. Pal and F. Kimura, 2006. Recognition of handwritten Kannada numerals. Proceeding of the 9th International Conference on Information Technology (ICIT'06), pp: 133-136.
CrossRef PMCid:PMC3710453
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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The authors have no competing interests.
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