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:
this https URL

本文介绍了 Bengali.AI-BRACU-OCR（bbOCR）：一种开源可扩展的文档光学字符识别系统，可将孟加拉语文档重构为结构化的可搜索的数字化格式，并提出了一种新颖的孟加拉语文本识别模型和两个合成数据集。全面的组件级和系统级评估结果表明，我们提出的解决方案优于当前最先进的孟加拉语 OCR 系统。