Scanned document OCR
Scanned document OCR with layout-aware extraction
Recover useful data from paper archives without treating every page as one flat transcript.
Scanning preserves an image of a page, not its semantic structure. The document may be searchable after OCR and still be difficult to use because columns, labels, stamps, and handwritten additions have been flattened.
Layout-aware extraction keeps the page as evidence while creating structured output for search, review, and export. This matters most for mixed archives where forms, letters, schedules, and attachments appear in the same batch.
Where scanned document ocr fits
- Paper archives and backfiles
- Signed or stamped forms
- Mixed document packets with several page layouts
How scanned document ocr works
- Prepare the scan: Remove blank pages, correct orientation, and keep page order and resolution intact.
- Classify pages: Separate cover sheets, forms, tables, correspondence, and attachments before applying a schema.
- Extract text and structure: Read typed content, key-value fields, tables, and clearly marked handwritten additions.
- Index and review: Store searchable text plus structured fields, source pages, and warnings for uncertain regions.
What the structured result can contain
| Field or structure | Example |
|---|
| Document type | Application form |
| Identifiers | Case 2026-1842 |
| Dates and parties | Submitted 2026-08-28 |
| Form fields | Status: Approved |
| Tables and notes | Schedule rows and reviewer note |
Archive scans carry physical-page problems
Dust, skew, bleed-through, staples, hole punches, and photocopy generations can remove or imitate characters.
- Check page count and ordering before extraction.
- Separate duplex bleed-through from real text.
- Review text covered by stamps, signatures, or punched holes.
- Keep the original scan immutable and store extracted data separately.
- Define retention and access rules before processing sensitive archives.
OCR API response design
Support asynchronous jobs for long packets and return page-level progress or errors.
Let callers specify a target schema when the archive contains a known form, while retaining a general text and layout result for unknown pages.
Read the document extraction API guide.
Common uses
Archive search
Add searchable text and identifiers to document collections that previously required manual browsing.
Form digitization
Capture recurring fields from scanned forms while retaining the signed page.
Backfile conversion
Turn historical schedules and tables into rows for controlled migration.
Free tools for this document
- PDF to JSON: Create structured JSON from PDF fields, sections, and repeating tables.
- PDF to Excel AI: Turn PDF tables and document fields into rows you can check before Excel.
Scanned document OCR questions
What resolution should scanned documents use for OCR?
A clear 300 DPI scan is a practical starting point for ordinary printed text. Small type, degraded originals, and handwriting may need more.
Can OCR remove stamps or signatures?
It should not alter the evidence. It may identify or ignore those regions during extraction, but the source scan should remain unchanged.
Can one batch contain different document types?
Yes. Page or document classification can route each item to the right schema, but classification errors should be visible to reviewers.