Optical character recognition, or OCR, converts text in images, scans and documents into machine-readable characters. It allows software to extract words and numbers from invoices, forms, receipts, identity documents and other files.
How does OCR work?
The system processes an image, identifies text regions and predicts the characters they contain. Modern document workflows may combine OCR with layout detection, language models and field-validation rules.
OCR vs. intelligent document processing
OCR reads characters. Intelligent document processing goes further by classifying documents, locating business fields, validating values and routing exceptions. OCR can be one component of that broader workflow.
What affects extraction accuracy?
- Image resolution and lighting
- Skew, blur and compression
- Handwriting or unusual fonts
- Complex tables and layouts
- Language and character set
- Damaged or incomplete documents
How should accuracy be measured?
Measure both character accuracy and field-level accuracy on representative documents. A page can look mostly correct while a critical invoice number, amount or bank detail is wrong. Track confidence scores and manual correction rates by field.
What controls are needed?
Validate extracted data against source documents, business rules and trusted master data. Route low-confidence or high-risk fields for human review, retain an audit trail and protect documents containing personal or financial information.
