文章基本信息

标题：Review of Offline Handwriting Recognition Techniques in the fields of HCR and OCR
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作者：Hemant Khandelwal ; Sakshi Gupta ; Arihant Kumar Jain 等
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2017
卷号：47
期号：3
页码：161-164
DOI：10.14445/22312803/IJCTT-V47P123
出版社：Seventh Sense Research Group
摘要：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 machineencoded 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.
关键词：Artificial Neural Network; Hidden Markov Model; HCR; OCR; Support Vector Machine.