How do you validate OCR results for tables?

We perform a visual alignment between the extracted table cells and the source image, checking for structural mismatches (missing rows/columns) and character-level OCR accuracy using bounding box analysis.

What is a character confusion matrix in OCR?

It's a report that shows which characters your OCR engine commonly misreads (like 'B' vs '8'). This helps you understand the specific OCR accuracy weaknesses in your scanned documents.

Can you validate OCR results from complex multi-page tables?

Yes. Our tool supports batch document validation for multi-page scans, preserving table continuity across pages and flagging fragmented structures.

How is this different from general data verification?

General verification checks semantic logic against source text. Our OCR validation focuses on visual image-to-text mapping—detecting misread pixels, broken borders, and structural misalignments unique to scanned tables.

Does it work with handwritten tables?

Yes, we validate OCR results from both printed and handwritten tables, focusing on character confidence scores and structural boundaries.

Validate OCR Table Results Against Source Images

Check the accuracy of tables extracted from images or PDFs. Our OCR validation tool compares extracted cells against the original document, flags structural errors, and ensures every row and column is correctly recognized.

Cell-by-cell comparisonStructure & boundary checkCharacter-level accuracy

From messy OCR output to perfectly validated tables

Structural Integrity

Automatically detect if OCR misaligned table columns, merged cells incorrectly, or misread border lines as text characters—common issues in scanned spreadsheets.

Character Precision

Catch the notorious OCR mistakes: '0' vs 'O', '5' vs 'S', or comma vs decimal point. We validate OCR accuracy at the character level to prevent data corruption.

Visual Overlay Diff

Overlay the extracted table directly onto the source image. See exactly where the OCR skipped a cell or inserted a phantom row, enabling rapid document validation.

How to validate OCR table extraction

1. Upload source image or PDF

Provide the original scanned document containing the tables you want to verify.

2. Review extracted results

Open the extracted results and inspect the structured results.

3. Generate verification report

Automatically compare extracted data against source documents and identify verified values, mismatches, unsupported fields, and missing evidence.

4. Trace evidence in the source image

Click any value to jump to the exact highlighted location in the original document.

5. Review and fix issues

Use the Artifacts workspace to correct mismatches, reconcile values, and prepare the final dataset.

6. Export trusted data

Use the Artifacts workspace to correct mismatches, reconcile values, and prepare the final dataset.

Specialized for OCR table validation

Evidence-backed cell verification

Every extracted value can be linked to supporting evidence from the source document. No more guessing where data came from.

Interactive source highlighting

Jump directly from a table cell to the exact location in the source document where the value was found.

Audit-ready verification reports

Generate audit-ready reports that summarize verified values, discrepancies, unsupported fields, and potential extraction issues.

Human-in-the-loop correction

Review flagged issues, update incorrect values, and create a clean final dataset before exporting.

Why validate OCR tables specifically?

Without OCR validation

× Hidden structural breaks in table rows
× Numeric '0' misread as 'O' causing calculation errors
× Misaligned headers break data pipelines
× No visibility into page-level OCR accuracy

With Gentables validation

✓ Visual structural diff highlights every broken cell
✓ Character-level confusion reports
✓ Automated header-to-data alignment checks
✓ High-confidence document validation audits

Perfect for scanned table workflows

Financial Statements & Reports

• Validate OCR results from scanned P&L statements

• Check OCR accuracy for numeric totals and line items

• Prevent data entry errors in financial dashboards

Invoice & Receipt Processing

• Validate extracted tables of line items and quantities

• Ensure unit prices and tax amounts are digitized correctly

• Accelerate AP workflow with reliable document validation

Scientific & Lab Data Sheets

• Verify OCR results from printed measurement tables

• Check special characters (μ, °C, ±) are recognized

• Maintain data integrity for research analysis

Validate OCR Table Results Against Source Images