Review of Offline Handwriting Recognition Techniques in the fields of HCR and OCR
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2017 by IJCTT Journal | ||
| Volume-47 Number-3 |
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| Year of Publication : 2017 | ||
| Authors : Hemant Khandelwal, Sakshi Gupta, Arihant Kumar Jain | ||
| DOI : 10.14445/22312803/IJCTT-V47P123 |
Hemant Khandelwal, Sakshi Gupta, Arihant Kumar Jain "Review of Offline Handwriting Recognition Techniques in the fields of HCR and OCR". International Journal of Computer Trends and Technology (IJCTT) V47(3):161-164, May 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Recently, numerous progressions have occurred in the area of Offline Handwriting Recognition, for example, Feature Extraction Techniques, Character Recognition Techniques and so on. HCR, Handwriting Character Recognition is the ability of a framework to interpret intelligible handwritten input from sources, for example, paper records, photos and might be sensed offline by Optical Scanning and Intelligent Word Recognition. Likewise OCR, Optical Character Recognition is the mechanical or electronic transformation of pictures of typed, manually written or printed content into machine-encoded content. It is a typical technique for digitizing printed writings and utilized as a part of machine procedures, for example, Cognitive Computing, Machine Translation and so forth. It is a field of research in Pattern Recognition, Artificial Intelligence and Computer Vision. The aim of this research is to actualize the different methods of offline handwriting recognition like, Support Vector Machine, Artificial Neural Network, Hidden Markov Model etc. in the fields of HCR and OCR. In this paper, different methods are analyzed and included to enhance programmed evaluation framework`s ease of use and enhance the character recognition system for the fields of HCR and OCR.
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Keywords
Artificial Neural Network, Hidden Markov Model, HCR, OCR, Support Vector Machine.