OPTICAL CHARACTER RECOGNITION

Optical Character Recognition (OCR) is indispensable for converting handwritten documents into analyzable, editable, and searchable data, given their prevalence in human transactions. Over the past decade, researchers have employed artificial intelligence and machine learning to automate document analysis, facilitating electronic conversion. This review paper aims to summarize and suggest research directions based on studies of handwritten document character recognition. Conducted as a Systematic Literature Review (SLR) covering articles from 2000 to 2019, it synthesizes and analyzes research articles collected from electronic databases. Through keyword searches and reference checks, 176 articles were selected, presenting state-of-the-art OCR techniques and identifying research gaps for future exploration.