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Article:An HCR System for Combinational Malayalam Handwritten Characters based on HLH Patterns
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 8 - Number 11 |
| Year of Publication: 2010 |
| Authors: Abdul Rahiman M, Aswathy Shajan, Rajasree M S |
10.5120/1250-1664
|
Abdul Rahiman M, Aswathy Shajan, Rajasree M S . Article:An HCR System for Combinational Malayalam Handwritten Characters based on HLH Patterns. International Journal of Computer Applications. 8, 11 ( October 2010), 19-23. DOI=10.5120/1250-1664
Abstract
An efficient and robust algorithm for recognition of handwritten Malayalam characters is proposed in this study. Malayalam, also known as Kairali, is one of the four major Dravidian languages of Southern India. It consists of basically 15 vowels and 36 consonants. The existence of lot of their combinations and connected characters, the recognition poses a gargantuan challenge in front of us. Till now Malayalam lacks an efficient OCR which meets all conditions. The intertwined characters are very complex owing to the non-adherent styles in which they may be presented. Here we propose an algorithm which uses the inveterate characteristic features to recognize these characters with perceptive accuracy by utilizing the intensity variations in the way in which they may be written. This algorithm recognizes the antediluvian script of Malayalam characters which are connected in nature. Here the input is a 24-bit bmp image which can be enscribed using the Light pen. The output is editable version of the recognized Malayalam characters. In our study we have classified the connected characters into 3 categories. The algorithm is tested for 3 sets of samples ranging 402 letters in noiseless environment and produces accuracy of 92%.
References
- D. Trier, A K Jain and T Taxt, “Feature Extraction methods for Character Recognition – A Survey”, Pattern Recognition, Vol 29, pp 641-662,1996.
- S N Srihari,X Yang and G R Ball, “ Offline Chinese Handwriting Recognition: an assessment of current Technology”, Front. Computer Science, China, Vol. 1 (2), pp 137-155, 2007.
- R. Seethalakshmi., T.R. Sreeranjani, T.Balachandar, Abnikant Singh, Markandey Singh, Ritwaj Ratan, and Sarvesh Kumar, “Optical Character Recognition for printed Tamil text using Unicode”, Journal of Zhejiang University SCI 6A(11) , pp.1297-1305, 2005.
- C. V. Lakshmi and C Patvardhan, “ A multi-font OCR system for printed Telugu text”, Proc. of Language engineering conference LEC, Hyderabad, pp.7-17, 2002.
- T. V. Ashwin and P. S. Sastry, “ A font and size independent OCR system for printed Kannada documents using support vector machines”, Saadhana, Vol. 27, Part 1, pp. 35–58,February 2002
- M Abdul Rahiman, Aewathy Shajan, Amala Elizabeth and M S Rajasree, “ Isolated Handwritten Malayalam Character recognition based on HLH intensity patterns”, Proc of International Conf on Machine leraning and computing, ICMLC 2009, Banglore, NOV 2009.
- Journal of Language Technology, Viswabharat@tdil, July 2003.
- M Abdul Rahiman and M S Rajasree, “Printed Malayalam Character Recognition Using Back propagation Neural Networks”, Proc.of IEEE International Advance Computing Conference (IACC 2009), Patiala, pp 1140-44, March 2009.
- Bindu Philip and R D Sudhakara Samuel, “ A Malayalam OCR system using column stochastic image matrix approach”, Proc of International Conf on Recent Technologies in communication and computing, Kottayam, December 2009.
- Neeba N V and C V Jawahar, “ Recognition of books by verification and retraining”, Proc of International Conf erence on Pattern Recognition, Florida, December 2008
- G Raju” Recognition of unconstrained handwritten Malayalam characters using zero crossings of wavelet coefficients”, Proc. of International Conference on Advanced Computing and Communications, ADCOM, pp 217-221, Dec 2006.
- Lajish V L,Suneesh T K K and Narayanan N K, “ Recognition of Isolated handwritten images using Kolmogorov-Smirnov Statistical classifier and K –nearest neighbor classifier”, Proc. Of International Conference on Cognition and Recognition, Mandya, Karnataka, December, 2005.
- Lajish V L, “ Handwritten Character Recognition using perpetual Fuzzy zoning and Class modular Neural Networks”, Proc. of fourth International Conf on Innovations in IT, 2007
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