Bridging the Gap: OCR Techniques for Noisy and Distorted Texts - Sanjay Kumar Gorai; Shekhar Pradhan (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
Optical Character Recognition (OCR) has evolved significantly over the years, enabling automated text extraction from a variety of sources. However, OCR systems often struggle with noisy and distorted texts, such as those found in low-quality scans, degraded historical documents, or images captured in challenging conditions. This paper explores state-of-the-art techniques and advancements in OCR for handling noisy and distorted texts. We discuss preprocessing methods, robust feature extraction, deep learning models, and post-processing techniques, providing a comprehensive overview of the field. Additionally, we analyse gaps in current research and propose future directions for developing more resilient OCR systems.