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Artificial Intelligence Review

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08-08-2020

Online handwriting recognition systems for Indic and non-Indic scripts: a review

Authors: Harjeet Singh, R. K. Sharma, V. P. Singh

Published in: Artificial Intelligence Review | Issue 2/2021

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Abstract

Handwriting recognition is one of the challenging tasks in the area of pattern recognition and machine learning. Handwriting recognition has two flavors, namely, Offline Handwriting Recognition and Online Handwriting Recognition. Though, saturation level has been achieved in machine printed (Offline) character recognition. Presently, due to dramatical development in IT sector, touch-based devices are available in the market with efficient processing capabilities. With this revolution, research in the area of handwriting recognition has become more popular in real-time (Online) mode. In this paper, a comprehensive review has been reported for online handwriting recognition of non-Indic and Indic scripts. The six non-Indic-scripts and eight Indic script namely, Arabic, Chinese, Japanese, Persian, Roman, Thai, and, Assamese, Bangla, Devanagari, Gurmukhi, Kannada, Malayalam, Tamil, Telugu, respectively have been considered in this article. This study comprises introduction of online handwriting recognition process, various challenges, motivations, feature extraction, and classification methodologies, used for recognizing the various scripting languages. Moreover, an effort has been made to provide the list of publicly available online handwritten dataset for various scripting languages. This study also provides the recognition and beneficial assistance to the novice researchers in field of handwriting recognition by providing a nut shell studies of various feature extraction strategies and classification techniques, used for the recognition of both Indic and non-Indic scripts.

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Title: Online handwriting recognition systems for Indic and non-Indic scripts: a review
Authors: Harjeet Singh
R. K. Sharma
V. P. Singh
Publication date: 08-08-2020
Publisher: Springer Netherlands
Published in: Artificial Intelligence Review / Issue 2/2021
Print ISSN: 0269-2821
Electronic ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-020-09886-7

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