A Review on Devanagari OCR for Handwritten Text - Bisht, Mamta; Gupta, Richa (Journal of Graphic Era University, 2026)
With the rapid growth of document digitization and multilingual content, robust Optical Character Recognition (OCR) systems have become increasingly important. While substantial progress has been achieved for Latin scripts, accurate text detection and recognition in complex Indic scripts, particularly Devanagari, remain challenging due to script-specific structural characteristics, handwriting variations, and limited benchmark datasets. This review paper presents a comprehensive and structured analysis of existing research on text detection, script identification, and handwritten numeral, character, and word recognition for the Devanagari script. The paper systematically categorizes and compares conventional image processing methods, machine learning techniques, and modern deep learning-based approaches, highlighting their strengths and limitations. In addition, key challenges related to segmentation, multilingual scenarios, degraded documents, and resource constraints are critically discussed. By identifying open research gaps and outlining potential future research directions, this work aims to serve as a valuable reference and roadmap for researchers and practitioners working on Devanagari OCR and multilingual document analysis.