Recognition of Handwritten Numerals of Manipuri Script
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10.5120/14674-2835 |
Chandan Jyoti Kumar and Sanjib Kumar Kalita. Article: Recognition of Handwritten Numerals of Manipuri Script. International Journal of Computer Applications 84(17):1-5, December 2013. Full text available. BibTeX
@article{key:article,
author = {Chandan Jyoti Kumar and Sanjib Kumar Kalita},
title = {Article: Recognition of Handwritten Numerals of Manipuri Script},
journal = {International Journal of Computer Applications},
year = {2013},
volume = {84},
number = {17},
pages = {1-5},
month = {December},
note = {Full text available}
}
Abstract
In this paper a support vector machine based handwritten numerals recognition system of Manipuri Script (Meetei Mayek) is investigated. We have used various feature extraction technique such as background directional distribution (BDD), zone based diagonal, projection histograms and Histogram Oriented Gradient features. In Background Directional Distribution (BDD) features background distribution of neighboring background pixels to foreground pixels in 8-different directions is considered forming a total of 128 features. For the computation of diagonal features, the whole image is divided into 64 zones of equal dimension each of size 4×4 pixels then features are extracted from the pixels of each zone by moving along the diagonal, thus consisting of 64 features in total. Projection Histograms count the number of foreground pixels in different directions such as vertical, horizontal, horizontal, left diagonal and right diagonal creating a total of 190 features. The HOG based feature is computed over the validation data set, was achieved by means of 9 rectangular cells and 9 bin histogram per cell Different combinations of these features are used for forming various feature vectors. These feature vectors are classified by using SVM classifier as 5-fold cross validation with RBF (radial basis function) kernel. Experimental results show that the proposed system performs well with the combined features and is robust to the writing variations that exist between persons and for a single person at different instances, thus being promising for user independent recognition of Meetei Mayek numeral.
References
- Vassilis Papavassiliou, Themos Stafylakis, Vassilis Katsouros and George Carayannis, "Handwritten document image segmentation into text lines and words. " Pattern Recognition 43,2010.
- Plamondon. R. , and S. Srihari "Online and offline Handwriting Recognition : A Comprehensive Survey. " IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol. 22 No. 1, 2000.
- D. N. S Bhat and M. S. Ningomba , "Manipuri Grammar", Central Institute of Indian Languages,1995.
- Chungkham Yashawanta Singh, Manipuri Grammar, Rajesh Publications,New Delhi, 2000.
- R M K Sinha, " A journey from Indian scripts processing to Indian language processing" , IEEE Ann. Hist. Computer, vol 31, no 1, pp 831, 2009
- Tangkeshwar Thokchom, P. K. Bansal, Renu Vig and Seema Bawa, "Recognition of Handwritten Character of Manipuri Script", Journal Of Computers, Vol. 5, No. 10, Oct 2010.
- N. Sharma, U. Pal, F. Kimura, and S. Pal, "Recognition of offline hand-written Devnagari characters using quadratic classifier," inProc. Indian Conference. Of Computer. Vision. Graph. Image Processing, 2006, pp. 805–816.
- Subhadip Basu , Nibaran Das, Ram Sarkar, Mahantapas Kundu,Mita Nasipuri and Dipak Kumar Basu, "Handwritten Bangla alphabet recognition using an MLP based classifier", 2nd National Conf. On Computer Processing of Bangla, Pp. 285-291, Feb-2005, Dhaka.
- U. Pal, T. Wakabayashi and F. Kimura, "Handwritten Bangla Compound Character Recognition using Gradient Feature" , 10th International Conference on Information Technology,2007.
- Sandhya Arora, Debotosh Bhattacharjee, Mita Nasipuri, L. Malik , M. Kundu and D. K. Basu, "Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition", IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 3, May 2010.
- Anita Rani, Rajneesh Rani and Renu Dhir , "Combination of Different Feature Sets and SVM Classifier for Handwritten Gurumukhi Numeral Recognition", International Journal of Computer Applications (0975 – 888) Volume 47– No. 18, June 2012.
- Anita Rani, Rajneesh Rani and Renu Dhir,"Diagonal Features and SVM Classifier for Handwritten Gurumukhi Character Recognition", International Journal of Advanced Research in Computer Science and Software Engineering Volume 2, Issue 5, May 2012.
- Mahesh Jangid, "Devanagari Isolated Character Recognition by using Statistical features", International Journal on Computer Science and Engineering (IJCSE) Vol. 3 No. 6 June 2011.
- Ratnashil N Khobragade, Dr. Nitin A. Koli and Mahendra S Makesar , "A Survey on Recognition of Devnagari Script", International Journal of Computer Applications & Information Technology Vol. II, Issue I, January 2013.
- Manal A. Abdullah, Lulwah M. Al-Harigy, and Hanadi H. Al-Fraidi, "Off-Line Arabic Handwriting Character Recognition Using Word Segmentation" Journal Of Computing, Vol. 4, Issue 3, Mar 2012.
- Hande Adiguzel, Emre Sahin and P?nar Duygulu, "A Hybrid Approach for Line Segmentation in Handwritten Documents" , International Conference on Frontiers in Handwriting Recognition ,2012.
- Thoudam Doren Singh , "Taste of Two Different Flavours: Which Manipuri Script Works Better" Proceedings of the 7th Workshop on Syntax, Semantics and Structure in Statistical Translation, pages 11–18, Atlanta, Georgia, 13 June 2013.