Title: Empirical review on handwritten Devanagari script recognition techniques using AI approaches

Authors: Swati Jaiswal; Kartik Chaudhari; Suraj Tade; Shrushti Khirwadkar; Atharva Pande

Addresses: Pimpri Chinchwad College of Engineering, Pune, India ' Pimpri Chinchwad College of Engineering, Pune, India ' Pimpri Chinchwad College of Engineering, Pune, India ' Pimpri Chinchwad College of Engineering, Pune, India ' Pimpri Chinchwad College of Engineering, Pune, India

Abstract: The digitisation of handwritten documents plays a crucial role in facilitating access, editing, and long-term preservation of data. The Devanagari script, serving as a pillar for various Indian language scripts, presents a unique challenge due to the lack of official digitising tools. This study focuses on the comprehensive analysis of methods employed for recognising offline, handwritten Hindi characters, with the ultimate objective of developing a system that can accurately convert full phrases into digital form. While existing research predominantly concentrates on character-level recognition, this work covers all the key steps involved in word recognition, ranging from database processing to character identification and integration of recognised words into coherent sentences. By addressing each facet of Hindi character recognition, this study contributes to the advancement of digitisation techniques for the Devanagari script, enabling efficient access and manipulation of handwritten Hindi documents.

Keywords: Devanagari script; handwriting recognition; digitisation; character recognition; languages.

DOI: 10.1504/IJCRC.2024.138219

International Journal of Creative Computing, 2024 Vol.2 No.2, pp.119 - 137

Received: 23 Feb 2023
Accepted: 02 Jun 2023
Published online: 30 Apr 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article