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Bridging the Gap: OCR Techniques for Noisy and Distorted Texts

Author

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  • Sanjay Kumar Gorai
  • Shekhar Pradhan

Abstract

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However, OCR systems often struggle with noisy and distorted texts, such as those found in low-quality scans, degraded historical documents, or images captured in challenging conditions.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.

Suggested Citation

  • Sanjay Kumar Gorai & Shekhar Pradhan, 2025. "Bridging the Gap: OCR Techniques for Noisy and Distorted Texts," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 695-703, February.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:726
    DOI: 10.32628/CSEIT2511111
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2511111
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