The Challenge
Historical documents with faded ink, stains, and irregular layouts caused standard OCR line detection to fail, resulting in poor text extraction accuracy.
Our Solution
Developed a hybrid approach combining traditional computer vision with deep learning to robustly identify text lines even in challenging conditions, with special handling for curved baselines and interlinear annotations.
Technologies Used
Results & Impact
- Improved line detection accuracy from 68% to 94%
- Reduced OCR character error rate by 40%
- Enabled digitization of previously unprocessable documents