Despite the existence of numerous Optical Character Recognition (OCR) tools, the lack of comprehensive open-source systems hampers the progress of document digitization in various low-resource languages, including Bengali. Low-resource languages, especially those with an alphasyllabary writing system, suffer from the lack of large-scale datasets for various document OCR components such as word-level OCR, document layout extraction, and distortion correction; which are available as individual modules in high-resource languages. In this paper, we introduce Bengali.AI-BRACU-OCR (bbOCR): an open-source scalable document OCR system that can reconstruct Bengali documents into a structured searchable digitized format that leverages a novel Bengali text recognition model and two novel synthetic datasets. We present extensive component-level and system-level evaluation: both use a novel diversified evaluation dataset and comprehensive evaluation metrics. Our extensive evaluation suggests that our proposed solution is preferable over the current state-of-the-art Bengali OCR systems. The source codes and datasets are available here: https://bengaliai.github.io/bbocr.
@article{arxiv.2308.10647,
title = {bbOCR: An Open-source Multi-domain OCR Pipeline for Bengali Documents},
author = {Imam Mohammad Zulkarnain and Shayekh Bin Islam and Md. Zami Al Zunaed Farabe and Md. Mehedi Hasan Shawon and Jawaril Munshad Abedin and Beig Rajibul Hasan and Marsia Haque and Istiak Shihab and Syed Mobassir and MD. Nazmuddoha Ansary and Asif Sushmit and Farig Sadeque},
journal= {arXiv preprint arXiv:2308.10647},
year = {2023}
}