bbOCR: An Open-source Multi-domain OCR Pipeline for Bengali Documents (2308.10647v2)
Abstract: 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.
- Imam Mohammad Zulkarnain (2 papers)
- Shayekh Bin Islam (10 papers)
- Md. Zami Al Zunaed Farabe (2 papers)
- Md. Mehedi Hasan Shawon (6 papers)
- Jawaril Munshad Abedin (2 papers)
- Beig Rajibul Hasan (1 paper)
- Marsia Haque (1 paper)
- Istiak Shihab (1 paper)
- Syed Mobassir (1 paper)
- MD. Nazmuddoha Ansary (5 papers)
- Asif Sushmit (8 papers)
- Farig Sadeque (14 papers)