Improve OCR Accuracy on Old or Poor Scans
Repair skew, bleed-through and weak contrast before expecting better recognition.
Start with the real problem
Do not optimize the format blindly. First identify whether the source is native text, a scan, a photo, or a mixture. That determines which transformation can save space or recover structure without destroying useful information.
Technical detail worth knowing
Historical scans can suffer from ink bleed and uneven paper tone. Tesseract documentation specifically discusses erosion/dilation, binarization and deskewing because character shape and line geometry strongly affect recognition.
Keep the original. Make one deliberate transformation, inspect the derivative, and only then decide whether another step is justified. Repeated lossy conversions compound artifacts and make diagnosis harder.
A controlled workflow
- Do not optimize the format blindly. First identify whether the source is native text, a scan, a photo, or a mixture. That determines which transformation can save space or recover structure without destroying useful information.
- Keep the original. Make one deliberate transformation, inspect the derivative, and only then decide whether another step is justified. Repeated lossy conversions compound artifacts and make diagnosis harder.
- Check the output at the size and in the application where it will actually be used. Verify small text, page order, selectable text when expected, tables, dates, identifiers, and the final file size or destination requirement.
Common failure modes
- Re-running the same conversion without changing the input problem.
- Judging quality only from a thumbnail preview.
- Deleting the source before the derivative has passed its acceptance check.
Acceptance test
Check the output at the size and in the application where it will actually be used. Verify small text, page order, selectable text when expected, tables, dates, identifiers, and the final file size or destination requirement.
Where FilexFlow fits
FilexFlow can perform the conversion step, but it cannot guarantee that OCR inferred every character correctly or that a third-party portal will accept a file. Treat the result as a derivative that still needs a human acceptance check.
Repair skew, bleed-through and weak contrast before expecting better recognition.
Related guides and tools
Technical source
https://tesseract-ocr.github.io/tessdoc/ImproveQuality.html
Last reviewed: 2026-09-15

