Versatile Bengali OCR: Document Analysis Technique for Varied Document Styles and Content

AKM Shahariar Azad Rabby, Hasmot Ali, Md. Majedul Islam, Fuad Rahman

Abstract: In our research paper, we introduce a distinctive Bengali OCR system that boasts impressive capabilities. This system excels in reconstructing document layouts while maintaining the integrity of structure, alignment, and even images. It integrates advanced image and signature detection for precise extraction. Specifically, tailored models for word segmentation accommodate various document types, such as computer-compose, letterpress, typewritten, and handwritten documents. Notably, the system handles static and dynamic handwritten inputs, recognizing diverse writing styles. Additionally, it achieves remarkable recognition of compound characters in the Bengali language. The comprehensive data collection contributes to a diverse corpus, and sophisticated technical components enhance character and word recognition. Other notable features include image, logo, signature recognition, table recognition, perspective correction, layout reconstruction, and a queuing module for efficient and scalable processing. The system showcases exceptional performance in the efficient and accurate extraction and analysis of text.