Handwritten Hindi character recognition: a review

被引:13
作者
Yadav, Madhuri [1 ]
Purwar, Ravindra Kumar [1 ]
Mittal, Mamta [2 ]
机构
[1] Guru Govind Singh Indrapratha Univ, USIC&T, Delhi, India
[2] GB Panth Govt Engn Coll, Dept Comp Sci & Engn, Delhi, India
关键词
QUADRATIC DISCRIMINANT FUNCTION; DEEP NEURAL-NETWORKS; IMAGE CLASSIFICATION; DEVNAGARI CHARACTERS; DIGIT RECOGNITION; SKEW DETECTION; DECISION; ALGORITHM; NORMALIZATION; SEGMENTATION;
D O I
10.1049/iet-ipr.2017.0184
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As the years passed by, computers became more powerful and automation became the need of generation. Humans tried to automate their work and replace themselves with machines. This effort of transition from manual to automatic gave rise to various research fields, and document character recognition is one such field. From the last few years, there is a sincere contribution from researchers for the development of optical character recognition systems for various scripts and languages. As a result of intensive research and development, there has been a significant improvement in handwritten devnagari text recognition. The main focus of this study is detailed survey of existing techniques for recognition of offline handwritten Hindi characters. It addresses all the aspects of Hindi character recognition starting from database to various phases of character recognition. The most relevant techniques of preprocessing, feature extraction and classification are discussed in various sections of this study. Moreover, this study is a zest of work accepted and published by research community in recent years. This study benefits its readers by discussing limitations of existing techniques and by providing beneficial directions of research in this field.
引用
收藏
页码:1919 / 1933
页数:15
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