Enhancing optical character recognition capabilities for Bengali script: the development and evaluation of Bengali CharNet

Abstract

Optical Character Recognition (OCR) technology has made an excellent stride in recent years, yet the accurate digitization of Bengali handwritten script remains a formidable challenge. This project introduces ’Bengali CharNet’, an improved deep learning-based model, specifically designed to advance OCR capabilities for Bengali handwriting, which is notably intricate and diverse in its character composition. The project aims to fill a crucial gap in OCR technology’s effectiveness with complex scripts like Bengali, which is the seventh most-spoken language in the world. The results of this research project are significant, with Bengali CharNet demonstrating a remarkable improvement in accuracy, precision, and recall compared to existing OCR models. The model achieved an overall accuracy of 96.8%, showcasing its effectiveness in recognizing and digitizing Bengali handwritten characters. This achievement represents a substantial advancement in the field of OCR, particularly for scripts that possess a high degree of complexity.