A review of optical character recognition system
DOI:
https://doi.org/10.32972/dms.2017.005Keywords:
optical character recognition, OCR, image acquisition, pre-processing, segmentation, feature extractionAbstract
Optical character recognition (OCR) has been a topic of great interest for many years. It is a system that permits us to convert various types of documents into machine encoded/computer-readable text. It consist of steps like image acquisition, pre- processing, segmentation, feature extraction, etc. The purpose of this work is to summarize the researches performed in the OCR field. It provides an overview of different aspects of OCR and discusses corresponding proposals aimed at resolving problems of OCR. A practical OCR problem is also investigated.
References
Bhansali, M.-Kumar, P.: An Alternative Method for Facilitating Cheque Clearance Using Smart Phones Application. International Journal of Application or Innovation in Engineering & Management (IJAIEM), 2013, 2 (1), 211-217.
Qadri, M. T.-Asif, M.: Automatic Number Plate Recognition System for Vehicle Identification Using Optical Character Recognition presented at International Conference on Education Technology and Computer, Singapore, 2009, Singapore, IEEE. https://doi.org/10.1109/ICETC.2009.54
Chaudhuri, A.: Some Experiments on Optical Character Recognition Systems for different Languages using Soft Computing Techniques. Technical Report, Birla Institute of Technology Mesra, Patna Campus, India, 2010.
Cheriet, M.-Kharma, N.-Liu, C. L.-Suen, C. Y.: Character Recognition Systems: A Guide for Students and Practitioners. John Wiley and Sons, 2007. https://doi.org/10.1002/9780470176535
Rice, S. V.-Nagy, G.-Nartker, T. A.: Optical Character Recognition: An Illustrated Guide to the Frontier. The Springer International Series in Engineering and Computer Science, Springer US, 1999.
Lund, W. B.-Kennard, D. J.-Ringger, E. K.: Combining Multiple Thresholding Binarization Values to Improve OCR Output presented in Document Recognition and Retrieval XX Conference 2013, California, USA, 2013.
Arica, N.-Vural, F. T. Y.: An Overview of Character Recognition focused on Offline Handwriting, IEEE Transactions on Systems, Man and Cybernetics- Part C. Applications and Reviews, 2001, 31 (2), 216-233. https://doi.org/10.1109/5326.941845
Chaudhuri, A.: Some Experiments on Optical Character Recognition Systems for different Languages using Soft Computing Techniques. Technical Report, Birla Institute of Technology Mesra, Patna Campus, India, 2010.
Mollah, A. F.-Basu, S.-Das, N.-Sarkar, R.-Nasipuri, M.-Kundu, M.: Text/Graphics Separation and Skew Correction of Text Regions of Business Card Images for Mobile Devices. Journal of Computing, Vol. 2, Issue 2, February 2010.
Shaikh, N. A.-Shaikh, Z. A.-Ali, G.: Segmentation of Arabic text into characters for recognition presented in International Multi Topic Conference. IMTIC, Jamshoro, Pakistan, 2008. Pakistan, Springer. https://doi.org/10.1007/978-3-540-89853-5_4
Ciresan, D. C.-Meier, U.-Gambardella, L. M.-Schmidhuber, J.: Convolutional neural network committees for handwritten character classification presented in International Conference on Document Analysis and Recognition, Beijing, China, 2011, USA, IEEE. https://doi.org/10.1109/ICDAR.2011.229
