Review On Optical Character Recognition for Off-line Devanagari Handwritten Characters & Challenges

Authors

  • Deepu Kumar  M.Tech Scholar (Computer Science & Engineering), Ajay Kumar Garg Engineering College, Ghaziabad, India
  • Divya Gupta  Asst. Professor (Computer Science & Engineering), Ajay Kumar Garg Engineering College, Ghaziabad, India

Keywords:

Handwritten character recognition, Feature extraction & Classification, OCR comparison, Challenges, Applications.

Abstract

Off-line handwritten Devanagari script recognition is getting a brighter side of the research day by day. In India, millions of people use handwritten Devanagari script for documentation in northern and central parts of India. The optical character recognition for off-line Devanagari script has been improving day by day. Some innovative steps have been taken into consideration. A bunch of work has been also accounted on handwritten character recognition attempt for several Indian scripts, like Gurmukhi, Gujarati, Oriya, Telugu, Kannada, Tamil, Malayalam, etc. This Off-line handwritten Devanagari script recognition does not have enough reported works. As of late different techniques have been represented by the researchers in the direction of off-line handwritten Devanagari script recognition, many recognition systems for detached handwritten Devanagari characters present in the literature work. The objective of this review paper most desirable feature extraction techniques, as well as classification techniques used for the identification are reviewed in various segments of the paper. An effort is made to address the most crucial consequences reported so far and it is also tried to foreground the better directions of the research to date. This review paper is intended to serve as a guide for the readers, working in the field of off-line handwritten Devanagari character recognition.

References

  1. Pal, U. and Chaudhuri, B.B., 2004. Indian script character recognition: a survey. pattern Recognition, 37(9), pp.1887-1899.
  2. Pal, U., Wakabayashi, T. and Kimura, F., 2009, July. Comparative study of Devnagari handwritten character recognition using different feature and classifiers. In Document Analysis and Recognition, 2009. ICDAR'09. 10th International Conference on (pp. 1111-1115). IEEE.
  3. Jayadevan, R., Kolhe, S.R., Patil, P.M. and Pal, U., 2011. Offline recognition of Devanagari script: A survey. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41(6), pp.782-796.
  4. Ramteke AS, Rane ME. A Survey on Offline Recognition of Handwritten Devanagari Script. International Journal of Scientific & Engineering Research. 2012 May;3(5).
  5. Bag, S. and Harit, G., 2013. A survey on optical character recognition for Bangla and Devanagari scripts. Sadhana, 38(1), pp.133-168.
  6. Goyal, A., Khandelwal, K., and Keshri, P., 2010. Optical Character Recognition for Handwritten Hindi. CS229 Machine Learning, pp.1-5.
  7. Khare, Sonal, and Jaiveer Singh. "Handwritten Devanagari Character Recognition System: A Review." International Journal of Computer Applications 121.9 (2015).
  8. Dixit, A., Navghane, A., and Dandawate, Y., 2014, December. Handwritten Devanagari character recognition using wavelet-based feature extraction and classification scheme. In India Conference (INDICON), 2014 Annual IEEE (pp. 1-4). IEEE.
  9. Thakral, Binny, and Manoj Kumar. "Devanagari handwritten text segmentation for overlapping and conjunct characters-A proficient technique." Reliability, Infocom Technologies and Optimization (ICRITO)(Trends and Future Directions), 2014 3rd International Conference on. IEEE, 2014.
  10. Khanduja, Deepti, Neeta Nain, and Subhash Panwar. "A hybrid feature extraction algorithm for Devanagari script." ACM Transactions on Asian and Low-Resource Language Information Processing 15.1 (2016): 2.
  11. Singh, D., Saini, J.P. and Chauhan, D.S., 2015, March. Hindi character recognition using RBF neural network and directional group feature extraction technique. In Cognitive Computing and Information Processing (CCIP), 2015 International Conference on (pp. 1-4). IEEE.
  12. Jangid M, Srivastava S. Accuracy Enhancement of Devanagari Character Recognition by Gray level Normalization. InProceedings of the 7th International Conference on Computing Communication and Networking Technologies 2016 Jul 6 (p. 25). ACM.
  13. Kumar, Satish. "A study for handwritten Devanagari word recognition." Communication and Signal Processing (ICCSP), 2016 International Conference on. IEEE, 2016.
  14. Bathla AK, Gupta SK, Jindal MK. Challenges in recognition of Devanagari Scripts due to segmentation of handwritten text. InComputing for Sustainable Global Development (INDIACom), 2016 3rd International Conference on 2016 Mar 16 (pp. 2711-2715). IEEE.
  15. Sharma DV, Lehal GS. An iterative algorithm for segmentation of isolated handwritten words in Gurmukhi script. InPattern Recognition, 2006. ICPR 2006. 18th International Conference on 2006 Aug 20 (Vol. 2, pp. 1022-1025). IEEE.
  16. Bansal V, Sinha RM. Segmentation of touching characters in Devanagari. InProceedings CVGIP, Delhi 1998 (pp. 371-376).
  17. Kumar, M., Jindal, M.K., and Sharma, R.K., 2014. Segmentation of isolated and touching characters in offline handwritten Gurmukhi script recognition. International Journal of Information Technology and Computer Science, 6(2), pp.58-63.
  18. Manisha, C.N., Reddy, E.S. and Krishna, Y.S., 2016. Role of Offline Handwritten Character Recognition System in Various Applications. International Journal of Computer Applications, 135(2), pp.30-33.
  19. Shelke S, Apte S. A fuzzy-based classification scheme for unconstrained handwritten Devanagari character recognition. InCommunication, Information & Computing Technology (ICCICT), 2015 International Conference on 2015 Jan 15 (pp. 1-6). IEEE.
  20. Rojatkar DV, Chinchkhede KD, Sarate GG. Design and analysis of LRTB feature-based classifier applied to handwritten Devnagari characters: A neural network approach. InAdvances in Computing, Communications, and Informatics (ICACCI), 2013 International Conference on 2013 Aug 22 (pp. 96-101). IEEE.
  21. Acharya, S., Pant, A.K., and Gyawali, P.K., 2015, December. Deep learning based large scale handwritten Devanagari character recognition. In Software, Knowledge, Information Management and Applications (SKIMA), 2015 9th International Conference on (pp. 1-6). IEEE.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

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How to Cite

[1]
Deepu Kumar, Divya Gupta, " Review On Optical Character Recognition for Off-line Devanagari Handwritten Characters & Challenges, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.1364-1367, March-April-2018.