Machine Learning Algorithms for Handwritten Devanagari Character Recognition: A Systematic Review
DOI:
https://doi.org/10.46243/jst.2022.v7.i01.pp1-16Keywords:
Devanagari Script, Optical Character Recognition, Segmentation, Convolutional Neural Network (CNN), Support Vector Machine, Image Processing.Abstract
Devanagari Character Recognition is a system in which handwritten Image is recognized and converted into a digital form. Devanagari handwritten character recognition system is based on Deep learning technique,
which manages the recognition of Devanagari script particularly Hindi. This recognition system mainly has five
stages i.e. Pre-processing, Segmentation, Feature Extraction, Prediction and Post processing. This paper has analyzed the approach for recognition of handwritten Devanagari characters. There are various approaches to solve this. Some of the methods along with their accuracy and techniques used are discussed here. Depending upon the dataset and accuracies of each character the techniques differs.
References
Shailesh Acharya, Ashok Kumar Pant, Prashnna Kumar Gyawali. Deep Learning Based Large Scale Handwritten Devanagari Character Recognition, 2015 9th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
C. V. Lakshmi, R. Jain, and C. Patvardhan. Handwritten Devnagari numerals recognition with higher accuracy, in Proc. Int. onfut.Intell. Multimedia Appl., 2007
Shanthi N and Duraiswami K. A Novel SVM-based Handwritten Tamil character recognition system, Springer Pattern Analysis & Applications,Vol-13, No. 2, 173-180,2010
M. Hanmandlu, O. V. R. Murthy, and V. K. Madasu. Fuzzy Model based recognition of handwritten Hindi characters, in Proc. Int. Conf. Digital Image Comput. Tech. Appl., 2007
C. V. Jawahar, M. N. S. S. K. Pavan Kumar, S. S. Ravi Kiran. A Bilingual OCR for HindiTelugu Documents and its Applications, Proc. of the 11th ICPR, vol. II, pp. 200-203, 1992
C. Chandra Sekhar. Online Handwritten Character Recognition of Devanagari and Telugu Characters using Support Vector Machines, Tenth International Workshop on Frontiers in Handwriting Recognition, Universit éde Rennes 1, Oct 2006, La Baule (France). inria00104402
A. Chaudhuri. Optical Character Recognition Systems for Different Languages with Soft Computing, Studies in Fuzziness and Soft Computing 352, DOI 10.1007/978-3-319-50252-6_8
Veena Bansala and R M K Sinha. A Complete OCR for printed Hindi Text in Devnagari Script,IEEE 2002
R. J. Ramteke and S. C. Mehrotra. Feature extraction based on moment invariants for handwriting recognition, in Proc. IEEE Conf. Cybern. Intell. Syst., 2006
Sonika Narang, M K Jindal and Munish Kumar. Devnagari ancient documents recognition using statistical feature extraction techniques, MS received 19 July 2018; revised 14 November 2018; accepted 4 March 2019; published online 13 May 2019
Xiaohe Li, Xingming Zhang, Bin Yang, Siyu Xia. Character Segmentation in Text Line via Convolutional Neural Network, 2017 4th International Conference on Systems and Informatics (ICSAI)
D. T. Mane, U. V. Kulkarni. Visualizing and Understanding Customized Convolutional Neural Network for Recognition of Handwritten Marathi Numerals, IEEE Electron Device Lett., vol. 20, pp. 569–571, Nov. 1999
A. Negi, C. Bhagvathi, and B. Krishna. An OCR system for telugu. In Proc. of ICDAR, 2001
Shalini Puria, Satya Prakash Singh, An efficient Devanagari character classification in printed and handwritten documents using SVM, International Conference on Pervasive Computing Advances and Applications–PerCAA 2019
S. Kumar, Performance comparison of features on Devanagari handprinted dataset, Int. J. Recent Trends, vol. 1, 2009
S. D. Connel, R.M.K. Sinha and Anil K. Jain, Recognition of Unconstraint On-Line Devanagari Characters, Proceedings of the International Conference on Pattern Recognition, 2000
Khandja D., Nain N., and Panwara S.: Hybrid feature extraction algorithm for Devanagari script, ACM Trans. Asian Low Resour. Lang. Inf. Process., 2015, 15, (1), p. 2:1–2:10
Pal U., Wakabayashi T., and Kimura F.: Comparative study of devnagari handwritten character recognition using different feature and classifiers. Int. Conf. Document Analysis and Recognition, Barcelona, Spain, July 2009, pp. 1111–1115
Sarkhel R., Das N., and Das A. et al: A multi‐scale deep quad tree based feature extraction method for the recognition of isolated handwritten characters of popular Indic scripts, Pattern Recognit., 2017, 71, pp. 78–93
Arora S., Bhattacharjee D., and Nasipuri M. et al: Combining multiple feature extraction techniques for handwritten devnagari character recognition. Third int. Conf. Industrial and Information Systems, Kharagpur, India, December 2008, pp. 1–6
S. Arora, D. Bhattacharjee, M. Nasipuri, L. Malik, Classification Of Gradient Change Features Using MLP for Handwritten Character Recognition, Emerging Applications of Information Technology (EAIT), Kolkata, India, 2006
Yadav M., and Purwar R.: Hindi handwritten character recognition using multiple classifiers. 7th Int. Conf. Cloud Computing, Data Science & Engineering–Confluence, Noida, India, Jan 2017, pp. 149–154
Khémiri, A., Echi, A. K., Belaïd, A., et al.: A system for off-line Arabic handwritten word recognition based on Bayesian approach. Int. Conf. Frontiers in Handwriting Recognition (ICFHR), Shenzhen, China, October 2016, pp. 560–565
Verma G. K., Prasad S., and Kumar P.: Handwritten Hindi character recognition using curvelet transform. Int. Conf. Information Systems for Indian Language, Patiala, India, 2011, pp. 224–227
A. Mohite and S. Shelke, Handwritten Devanagari Character Recognition using Convolutional Neural Network, 2018 4th International Conference for Convergence in Technology (I2CT), Mangalore, India, 2018, pp. 1-4, doi: 10.1109/I2CT42659.2018.9057991
Deore, S.P., Pravin, A. Devanagari Handwritten Character Recognition using fine-tuned Deep Convolutional Neural Network on trivial dataset. Sādhanā 45, 243 (2020). https://doi.org/10.1007/s12046-020-01484-1
S. Prabhanjan and R. Dinesh, Deep learning approach for devanagari script recognition, Int. J. Image Graph. 17(3) (2017) 1750016. https://doi.org/10.1142/S0219467817500164
Pankaj Kale, Arti V. Bang, and Devashree Joshi, Recognition Of Handwritten Devanagari Characters Using Machine Learning Approach, International Journal of Industrial Electronics and Electrical Engineering, ISSN: 2347-6982, Volume-3, Issue-9, pp. 48- 51, Sept.-2015
R.M.K. Sinha and H.N. Mahabala, Machine recognition of Devanāgarī script, IEEE Transactions on Systems, Man and Cybernetics, 9(8), 1979, pp. 435-441
Support Vector Machines for Binary Classification, Available at: https://www.mathworks.com/help/stats/support-vector-machines-forbinary-classification.html
Pechwitz, M., Maddouri, S. S., Märgner, V., et al.: ‘IFN/ENIT–database of handwritten Arabic words’. Proc. 7th Colloque Int. Francophone sur l'Ecrit et le Document, Hammamet, Tunisia, October 2002, pp. 129–136
Altwaijry, N., Al-Turaiki, I. Arabic handwriting recognition system using convolutional neural network. Neural Comput & Applic (2020). https://doi.org/10.1007/s00521-020-05070-8
Bharath A and Madhvanath S 2009 Online handwriting recognition for Indic scripts. In: Guide to OCR for Indic scripts, pp. 209–234
Sharma N., Pal U., Kimura F., Pal S. (2006) Recognition of Off-Line Handwritten Devnagari Characters Using Quadratic Classifier. In: Kalra P.K., Peleg S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949619_72
Verma G.K., Prasad S., Kumar P. (2011) Handwritten Hindi Character Recognition Using Curvelet Transform. In: Singh C., Singh Lehal G., Sengupta J., Sharma D.V., Goyal V. (eds) Information Systems for Indian Languages. ICISIL 2011. Communications in Computer and Information Science, vol 139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19403-0_37
N. Aneja and S. Aneja, "Transfer Learning using CNN for Handwritten Devanagari Character Recognition," 2019 1st International Conference on Advances in Information Technology (ICAIT), Chikmagalur, India, 2019, pp. 293-296, doi: 10.1109/ICAIT47043.2019.8987286
S. Shitole and S. Jadhav, "Recognition of handwritten devanagari characters using linear discriminant analysis," 2018 2nd International Conference on Inventive Systems and Control (ICISC), Coimbatore, 2018, pp. 100-103, doi: 10.1109/ICISC.2018.8398991
Veena Bansal, R.M.K. Sinha, Segmentation of touching and fused Devanagari characters, Pattern Recognition, Volume 35, Issue 4, 2002, Pages 875-893,ISSN 0031-3203, https://doi.org/10.1016/S0031-3203(01)00081-4 www.jst.org.in 15 | Page
Garg N.K., Kaur L., Jindal M.K. (2011) The Segmentation of Half Characters in Handwritten Hindi Text. In: Singh C., Singh Lehal G., Sengupta J., Sharma D.V., Goyal V. (eds) Information Systems for Indian Languages. ICISIL 2011. Communications in Computer and Information Science, vol 139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19403-0_8
B. Dessai and A. Patil, "A Deep Learning Approach for Optical Character Recognition of Handwritten Devanagari Script," 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kannur, India, 2019, pp. 1160-1165, doi: 10.1109/ICICICT46008.2019.8993342
Bisht, M., Gupta, R. Offline handwritten Devanagari modified character recognition using convolutional neural network. Sādhanā 46, 20 (2021). https://doi.org/10.1007/s12046-020-01532-w
Y. Gurav, P. Bhagat, R. Jadhav and S. Sinha, "Devanagari Handwritten Character Recognition using Convolutional Neural Networks," 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), Istanbul, Turkey, 2020, pp. 1-6, doi: 10.1109/ICECCE49384.2020.9179193
