OCR PDF to Text

Worked example

Example: OCR a scanned invoice PDF and copy the line items into a spreadsheet instead of manual entry.

When to use this

• Pulling quotes from scanned books or articles.
• Migrating paper records into databases.
• Making scanned PDFs accessible to screen readers.

Common examples

• Phone photo scan of a receipt → searchable text export where you can copy line items after proofreading totals.
• Old faxed letter PDF → text extracted so keyword search works in document management systems.
• Multi-page handwritten notes scan → OCR quality depends on scan DPI; proofread before archiving.
• Five-page typed scan at 300 DPI → searchable PDF for keyword find in Preview.
• Historical newspaper clip scan → expect errors on faded serif fonts; proofread names.

Common mistakes

• Using phone photos with shadows and curl.
• Assuming table structure survives OCR without cleanup.
• Skipping proofread on financial documents.

How it works

Runs optical character recognition on scanned or image-heavy PDF pages to add a searchable text layer so you can find, copy, and convert content more reliably than from raw images alone.

Limitations

Text recognition accuracy depends on scan quality, fonts, and language. Review extracted text before relying on it for legal, medical, or financial decisions.

Privacy and file handling

Your data stays on your device and is not uploaded.

Formula or method

Word bounding boxes position invisible text over scanned page images. Pages containing native text are copied unchanged. Recognition is imperfect: review names and numbers. Export does not preserve digital signatures.