Introduction
Automate OCR processing for large document sets with consistent language and quality settings. This guide assumes you have a basic understanding of PDF files and builds on that knowledge with more detailed techniques and real-world scenarios. Whether you're using PDFly's free online tools or building your own workflow, this guide covers everything you need to know about batch ocr processing 100 scanned pdfs at once.
Understanding OCR
OCR (Optical Character Recognition) transforms scanned documents and images into searchable, selectable text. This technology is essential for working with scanned paperwork, making it searchable, editable, and accessible. Modern OCR engines achieve 99%+ accuracy on quality scans.
Key Concepts You Need to Know
- OCR accuracy depends on scan quality — 300 DPI is the recommended minimum
- Pre-processing (deskew, despeckle, binarize) dramatically improves OCR results
- Multi-language OCR requires language packs and script detection
- OCR creates a text layer over the image, preserving the original appearance
- AI-enhanced OCR achieves higher accuracy on handwriting and low-quality scans
Tips & Best Practices
Pre-process scans with deskewing and despeckling for best OCR accuracy
Use 300 DPI minimum for OCR — lower resolutions significantly reduce accuracy
Choose the correct language pack for documents in non-English languages
Review OCR output for common errors (0/O, 1/l/I, rn/m confusion)
Use batch OCR for large document sets to save time
Common Mistakes to Avoid
- Low-resolution scans produce poor OCR results with many errors
- Not selecting the correct language causes character recognition failures
- Skipping pre-processing steps significantly reduces accuracy
- Handwritten text is still challenging for most OCR engines
- Multi-column layouts may produce jumbled text without proper handling