Abstract
This paper deals with stroke-based online Bangla character recognition strategy. In the present work, constituent strokes have been extracted from characters and then popularly used distance based features have been estimated in order to recognize the basic strokes. Next, a rule-based approach is followed for the recognition of the characters from the previously recognized strokes. A total of 15,000 isolated online handwritten Bangla characters contributing 32,534 stroke samples have been used in this experiment, and a satisfactory result of 89.39% recognition accuracy has been achieved.
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References
Connell, S.D., Sinha, R.M.K., Jain, A.K.: Recognition of unconstrained online Devanagari characters. In: 15th International Conference on Pattern Recognition, pp. 368–371 (2000)
Joshi, N., Sita, G., Ramakrishnan, A.G., Deepu, V.: Machine recognition of online handwritten Devanagari characters. In: Proceedings of International Conference on Document Analysis and Recognition, pp. 1156–1160 (2005)
Swethalakshmi, H., Jayaraman, A., Chakravarthy, V.S., Sekhar, C.C.: On-line handwritten character recognition for Devanagari and Telugu scripts using support vector machines. In: Proceedings of International Workshop on Frontiers in Handwriting Recognition, pp. 367–372 (2006)
Swethalakshmi, H., Sekhar, C.C., Chakravarthy, V.S.: Spatiostructural features for recognition of online handwritten characters in Devanagari and Tamil scripts. In: Proceedings of International Conference on Artificial Neural Networks, vol. 2, pp. 230–239 (2007)
Kumar, A., Bhattacharya, S.: Online Devanagari isolated character recognition for the iphone using hidden markov models. In: International Conference on Students Technology Symposium, pp. 300–304 (2010)
Tripathi, A., Paul, S.S., Pandey, V.K.: Standardization of stroke order for online isolated Devanagari character recognition for iPhone. In IEEE International Conference on Technology Enhanced Education, pp. 1–5 (2012)
Kubatur, S., Sid-Ahmed, M., Ahmadi, M.: A neural network approach to online Devanagari handwritten character recognition. In: International conference on High Performance Computing and Simulation (2012). doi:10.1109/HPCSim.2012.6266913
Lajish, V.L., Kopparapu, S.K.: Online handwritten Devanagari stroke recognition using extended directional features. In: IEEE 8th International Conference on Signal Processing and Communication System (2014). doi:10.1109/ICSPCS.2014.7021063
Bhattacharya, U., Gupta, B.K., Parui, S.K.: Direction code based features for recognition of online Handwritten characters of Bangla. In: International Conference on Document Analysis and Recognition, pp. 58–62 (2007)
Parui, S.K., Guin, K., Bhattacharya, U., Chaudhuri, B.B.: Online handwritten Bangla character recognition using HMM. In International Conference on Pattern Recognition, pp. 1–4 (2008)
Bandyopadhyay, A., Chakraborty, B.: Development of online handwriting recognition system: a case study with handwritten Bangla character. In: World Congress on Nature and Biologically Inspired Computing, pp. 514–519 (2009)
Roy, R.: Stroke-database design for online handwriting recognition in Bangla. In: International Journal of Modern Engineering Research, pp. 2534–2540 (2012)
Bhattacharya, U., Banerjee, R., Baral, S., Dey, R., Parui, S.K.: A semi automatic annotation scheme for Bangla online mixed cursive handwriting samples. In: International Conference on Frontiers in Handwriting Recognition, pp. 680–685 (2012)
Biswas, C., Bhattacharya, U., Parui, S.K.: HMM based online handwritten Bangla character recognition using Dirichlet distributions. In: International Conference on Frontiers in Handwriting Recognition, pp. 600–605 (2012)
Ghosh, R.: A novel feature extraction approach for online Bengali and Devanagari character recognition. In: International Conference on Signal Processing and Integrated Networks, pp. 483–488 (2015)
Mondal, T., Bhattacharya, U., Parui, S.K., Das, K., Mandalapu, D.: On-line handwriting recognition of indian scripts—the first benchmark. In: 12th International Conference on Frontiers in Handwriting Recognition, pp. 200–205 (2010)
Sen, S.P., Paul, S.S., Sarkar, R., Roy, K., Das, N.: Analysis of different classifiers for on-line Bangla character recognition by combining both online and offline information. In: 2nd International Doctoral Symposium on applied computation and security Systems (2015)
Sen, S.P., Sarkar, R., Roy, K.: A simple and effective technique for online handwritten Bangla character recognition. In: 4th International Conference on Frontiers in Intelligent Computing: Theory and Application, pp. 201–209 (2015)
Sen, S.P., Bhattacharyya, A., Das, A., Sarkar, R., Roy, K.: Design of novel feature vector for recognition of online handwritten Bangla basic characters. In: 1st International Conference on Intelligent Computing and Communication (2016)
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Sen, S., Sarkar, R., Roy, K. (2017). An Approach to Stroke-Based Online Handwritten Bangla Character Recognition. In: Chaki, R., Saeed, K., Cortesi, A., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-10-3391-9_10
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DOI: https://doi.org/10.1007/978-981-10-3391-9_10
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