How OCR Works
Upload your image or PDF file. Our OCR engine processes the visual content and identifies text regions using pattern recognition algorithms.
Recognized text is assembled into a structured document preserving the original layout as closely as possible, including paragraphs and line breaks.
Why Use OCR?
OCR (Optical Character Recognition) technology analyzes image pixel patterns to identify text characters, enabling digital extraction from scanned documents and photos.
Extracted text becomes fully searchable, copyable, and editable, transforming static image content into productive digital data.
Common Uses for OCR
Digitize paper contracts, invoices, and forms into searchable PDFs or editable Word documents for faster processing and archival.
Extract text from book scans, academic papers, and handwritten notes to make the content indexable and shareable in digital workflows.
What Affects OCR Accuracy
Good scans give 95%+ accuracy: 300 DPI, high contrast (black text on white), straight pages, clear fonts. Poor scans reduce accuracy: blurry photos, faded text, skewed pages, unusual fonts. Handwriting is harder than printed text—expect mistakes.
Simple layouts work best: paragraphs, lists, basic tables. Complex layouts—multiple columns, text boxes, fancy formatting—may need manual cleanup after OCR. Always proofread OCR output before using it for important work.
Tips for Best Results
Scan at 300 DPI minimum. Ensure good contrast. Scan pages straight, not skewed. Use even lighting for photos—no shadows across text. Clear scans = accurate OCR.
Select the correct language before processing. After OCR, proofread the output—especially numbers, names, and technical terms. OCR makes mistakes. Check before you trust it.