Enhancement of Bengali OCR by Specialized Models and Advanced Techniques
  for Diverse Document Types
AKM Shahariar Azad Rabby Hasmot Ali Md. Majedul Islam Sheikh Abujar Fuad Rahman
This research paper presents a unique Bengali OCR system with some
capabilities. The system excels in reconstructing document layouts while
preserving structure, alignment, and images. It incorporates advanced image and
signature detection for accurate extraction. Specialized models for word
segmentation cater to diverse document types, including computer-composed,
letterpress, typewriter, and handwritten documents. The system handles static
and dynamic handwritten inputs, recognizing various writing styles.
Furthermore, it has the ability to recognize compound characters in Bengali.
Extensive data collection efforts provide a diverse corpus, while advanced
technical components optimize character and word recognition. Additional
contributions include image, logo, signature and table recognition, perspective
correction, layout reconstruction, and a queuing module for efficient and
scalable processing. The system demonstrates outstanding performance in
efficient and accurate text extraction and analysis.