Abstract

Handwriting Recognition System helps converting hand written text documents to digital form. Hand written recognition systems are different for different languages depending upon the script’s complexity. Extensive research have been performed on various languages across the globe including English but Devanagari Script has been left far behind due to its complex nature. This paper enlightens some of the popular research performed in recognizing Devanagari script. It also summarizes various advantage and scope of using different methodology including Bounding Box technique, Ostu’s algorithm, neural networks and many more.

References

• Hoyamoon S. M. Beigi : An Overview of Handwriting Recognition, Proceedings of the 1st Annual Conference on Technological Advancements in Developing Countries, Columbia University, July 24-25, pp. 30-46, New York (1993)
• Vikas J Dongre and Vijay H Mankar: A Review of Research on Devnagari Character Recognition, International Journal of Computer Applications Vol. 12– No.2, (November 2010)
• Nur Sukinah Aziz and Mohd Nizam Saad: Redesigning the User Interface of Handwriting Recognition System for Preschool Children, 2nd International Conference on Education Technology and Computer (ICETC), (2010)
• Mustafa Ali Abuzaraida, Akram M. Zeki and Ahmed M. Zeki Problems of Writing on Digital Surfaces in Online Handwriting Recognition Systems, 5th International Conference on Information and Communication Technology for the Muslim World, (2013)
• Felipe Mendonca Gouveia, Byron Leite Dantas Bezerra, Cleber Zanchettin and Jo˜ao Raul Jardim Meneses: Handwriting recognition system for mobile accessibility to the visually impaired people, IEEE International Conference on Systems, Man, and Cybernetics, (October, 2014)
• Neha Sahu and Nitin Kali Raman, “An Efficient Handwritten Devanagari Character Recognition System Using Neural Network, IEEE, pp. 173-177,(2013)
• Gaurav Jaiswal: Handwritten Devanagari Character Recognition Model Using Neural Network, International Journal of Engineering Development and Research(IJEDR), Vol. 2, Issue 1, (2014)
• Richa Patil and Varunakshi Bhojane: Character recognition of Devanagari characters using Artificial Neural Network, International Journal of Computational Engineering Research (IJCER), Vol. 05, Issue 02, (February, 2015)
• Kunal Shah, Jaideep Singh, Prashant Pushkarna, Hasnain Kurawadwala and Abhishek Alate: A New Approach for Segmentation of Devanagari Characters, Global Research Analysis(GRA), Vol. 2, Issue : 4, (April 2013)
• R. Jayadevan, Satish R. Kolhe, Pradeep M. Patil, Umapada Pal: Offline Recognition of Devanagari Script: A Survey, IEEE Transaction on Systems, Man and Cybernetics, Vol. 41, No. 6, (November 2011)
• R. J. Ramteke, S. C. Mehrotra: Feature Extraction Based on Moment Invariants for Handwriting Recognition, IEEE,( 2006)
• Chavan S. V., Kale K. V. Kazi M. M., Rode Y. S.: Recognition of Handwritten Devanagari Compound Character a Moment Feature Based Approach, International Journal of Machine Intelligence, Vol. 5, pp: 421-425, (April 2013)
• Ankita Karia, Sonali Sharma, Reevon Rodrigues, Maitreya Save” Character Recognition (Devanagari Script), International Journal of Engineering Research and Applications, Vol. 5, pp. 109-114,(April 2015)