National Journal of System and Information Technology

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Optical Character Recognition Using Deep Learning – A Technical Review


Affiliations
1 BMIIT, India
2 Babu Madhav Institute of Information Technology, Uka Tarsadia University-Bardoli, India
     

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OCR is used to identify the character from human written text. To recognize the text segmentation of character is important stage. So here, we addressed different techniques to recognize the character. This document also presents comparison of different languages for character and numeral recognition with its accuracy achieved by different writer. Segmentation problem of each language were different also handwritten character was also varied user to user, so it is necessary to make OCR systems more effective and accurate for segmentation. Comparative study concludes that deep learning technique gives good segmentation and gives better result in case with large dataset compares to other techniques.

Keywords

OCR, Deep Learning, CNN.
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  • Shailesh Acharya, Ashok Kumar Pant, Prashnna Kumar Gyawali,” Deep Learning Based Large Scale Handwritten Devanagari Character Recognition”, 9th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 2015.

  • Jenis J. Macwan, Mukesh M. Goswami, Archana N. Vyas, “A Survey on Offline Handwritten North Indian Script Symbol Recognition”, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) – 2016.

  • Shruthi A , M S Patel,” Offline Handwritten Word Recognition using Multiple Features with SVM Classifier for Holistic Approach” , International Journal of Innovative Research in Computer and Communication Engineering, June 2015.

  • Akm Ashiquzzaman and Abdul Kawsar Tushar,” Handwritten Arabic Numeral Recognition using Deep Learning Neural Networks”, 2011.

  • Darmatasia and Mohamad Ivan Fanany,” Handwriting Recognition on Form Document Using Convolutional Neural Network and Support Vector Machines”, 2017 Fifth International Conference on Information and Communication Technology (ICoICT), 2017.

  • Chaouki Boufenar , Adlen Kerboua, Mohamed Batouche,” Investigation on deep learning for off-line handwritten Arabic character recognition”, Cognitive Systems Research, 2017.

  • WeixinYang , LianwenJin , DachengTao , ZechengXie , ZiyongFeng, “A new training method to enhance deep convolutional neural networks for large-scale unconstrained handwritten Chinese character recognition”.

  • Jangid, Mahesh, et al. "SVM classifier for recognition of handwritten Devanagari numeral.” Image Information Processing (ICIIP), 2011 International Conference on. IEEE, 2011.

  • Bhattacharya, U., et al., "Neural combination of ANN and HMM for Handwritten Devanagari numeral recognition.” Tenth International Workshop on Frontiers in Handwriting Recognition. Suvisoft, 2006.

  • Mehrotra, Kapil, et al., "Unconstrained handwritten Devanagari character recognition using convolutional neural networks.” Proceedings of the 4th International Workshop on Multilingual OCR. ACM, 2013.

  • Jitendra V. Nasriwala, Dr. Bankim C. Patel, “Offline Handwritten Gujarati Character Recognition Based on Water Reservoir and Radial Histogram”, International Journal of Electrical Electronics & Computer Science Engineering, 2016.

  • C. Patel, and A. A. Desai, “Gujarati Handwritten Character Recognition Using Hybrid Method Based On Binary Tree-Classifier And K-Nearest Neighbor”. International Journal of Engineering Research and Technology, ESRSA Publications. (Vol. 2, No. 6). June-2013.

  • Jenis J. Macwan, Mukesh M. Goswami, Archana N. Vyas, “A Survey on Offline Handwritten North Indian Script Symbol Recognition”, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) – 2016.


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  • Optical Character Recognition Using Deep Learning – A Technical Review

Abstract Views: 433  |  PDF Views: 3

Authors

Preeti P. Bhatt
BMIIT, India
Isha Patel
Babu Madhav Institute of Information Technology, Uka Tarsadia University-Bardoli, India

Abstract


OCR is used to identify the character from human written text. To recognize the text segmentation of character is important stage. So here, we addressed different techniques to recognize the character. This document also presents comparison of different languages for character and numeral recognition with its accuracy achieved by different writer. Segmentation problem of each language were different also handwritten character was also varied user to user, so it is necessary to make OCR systems more effective and accurate for segmentation. Comparative study concludes that deep learning technique gives good segmentation and gives better result in case with large dataset compares to other techniques.

Keywords


OCR, Deep Learning, CNN.

References