OCR for Printed Bangla Characters Using Neural Network

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Author(s)

Asif Isthiaq 1,* Najoa Asreen Saif 1

1. Department of Computer Science and Engineering, Ahsanullah University of Science and Technology, 141&142, Love Road, Tejgaon Industrial Area, Dhaka 1208, Bangladesh

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2020.02.03

Received: 28 Oct. 2019 / Revised: 10 Nov. 2019 / Accepted: 23 Nov. 2019 / Published: 8 Apr. 2020

Index Terms

Dataset Creation, Neural Network, Training Model, Testing Model, Classification

Abstract

Optical Character recognition is a buzzword in the field of computing. Artificial neural networks are being used to recognize characters for a long time. ANN has the ability to learn and model non-linear and complex relationships, which is really important because in real life, many of the relationships between inputs and outputs are non-linear as well as complex. Research in the field of OCR with Bangla language is not as vast as the English language. So, there is a scope of research in this area. It can be used to search and scan hundreds of Bangla documents within seconds and can easily manipulate the data. It is developed for various purpose like for vision impaired person where OCR software can help turn books, magazines and other printed documents into accessible files that they can listen. The limitation of traditional OCR are sufficient dataset is not available, all different font of characters are not available and there are lots of complex and similar shape characters for which accuracy not good. In our research, we first tried to make a dataset large enough so that we can train our neural network as they require big data to train. We built our own dataset of 2,97,898 Bangla single character images of different fonts . Then for implementing neural network we used Scikit-learn’s multi-layer perceptron classifier and we also implemented our own multi-layer feed forward back propagation neural network using a machine learning framework named Tensorflow. We have also built a GUI application to demonstrate the recognition of Bangla single character images.

Cite This Paper

Asif Isthiaq, Najoa Asreen Saif, " OCR for Printed Bangla Characters Using Neural Network", International Journal of Modern Education and Computer Science(IJMECS), Vol.12, No.2, pp. 19-29, 2020.DOI: 10.5815/ijmecs.2020.02.03

Reference

[1]Raghuraj Singh1, C. S. Yadav2, Prabhat Verma3,Vibhash Yadav4, Optical Character Recognition (OCR) for Printed Devnagari Script Using Artificial Neural Network International Journal of Computer Science Communication,Vol. 1, No. 1, January- June 2010
[2]Dr.Mrs.V.V.Patil 1, Rajharsh Vishnu Sanap 2 , Rohini Babanrao Kharate,Optical Character Recognition Using Artificial Neural Network,International Journal of Engineering Research and General Science, Volume 3, Issue 1, January-February, 2015
[3]V. Kalaichelvi,Ahammed Shamir Ali, Application of Neural Networks in Character Recognition International Journal of Computer Applications (0975 8887), Volume 52 No.12, August 2012
[4]Shyla Afroge, Boshir Ahmed, Firoz Mahmud, Optical Character Recognition using Back Propagation Neural Network 2nd International Conference on Electrical, Computer Telecommunication Engineering (ICECTE), 8-10 December 2016
[5]Md. Shahiduzzaman, Bangla Hand Written Character Recognition International Journal of Science and Research (IJSR), Index Copernicus Value (2013): 6.14, 2013
[6]Riasat Azim,Wahidur Rahman, M. Fazlul Karim, Bangla Hand Written Character Recognition Using Support Vector Machine. International Journal of Engineering Works, Vol. 3, Issue 6, PP. 36-46, June 2016
[7]Chirag I Patel, Ripal Patel, Palak Patel, Handwritten Character Recognition using Neural Network. International Journal of Scientific Engineering Research, Volume 2, Issue 5,May-2011
[8]Adnan SHatil,Mumit Khan, Minimally Segmenting High Performance Bangla Optical Character Recognition Using Kohonen Network
[9]Md. Mahbub Alam and Dr. M. Abul Kashem, A Complete Bangla OCR System for Printed Chracters COPYRIGHT 2010 JCIT, ISSN 2078-5828 (PRINT), ISSN 2218-5224 (ONLINE),VOLUME 01, ISSUE 01, 2010
[10]Abdur Rahim Md. Forkan, Shuvabrata Saha, Md. Mahfuzur Rahman, Md. Abdus Sattar, RECOGNITION OF CONJUNCTIVE BANGLA CHARACTERS BY ARTIFICIAL NEURAL NETWORK International Conference on Information and Communication Technology, 7-9 March 2007