What is OCR?
OCR analyzes images containing text and converts it into machine-readable character data. Without OCR, a scan is just a picture; with OCR, it becomes editable text.
- Optical Character Recognition (OCR)
- Technology using pattern recognition and ML to identify text characters in images. Modern OCR achieves 90-99% accuracy.
How OCR Works
- Preprocessing: Grayscale, contrast, noise removal, skew correction.
- Layout analysis: Detect text regions, columns, paragraphs.
- Character segmentation: Break lines into characters.
- Recognition: Compare against trained models.
- Post-processing: Language models correct errors.
- Output: Editable text with optional position data.
AI OCR vs Traditional
| Aspect | AI OCR (Gemini/GPT-4) | Traditional (Tesseract) |
|---|---|---|
| Printed text | 95-99% | 85-95% |
| Handwritten | 70-85% | 40-60% |
| Multi-language | Excellent (auto) | Good (manual selection) |
| Complex layouts | Tables, columns, forms | Struggles |
| Location | Cloud | Local (browser) |
| Privacy | Image sent to cloud | On-device |
Key Difference: AI OCR understands context — reads "Dr. Smith" correctly on blurry scans. Traditional OCR only sees pixel patterns.
Tips for Best Accuracy
- 300 DPI minimum scan resolution
- Good, even lighting
- Keep text straight
- High contrast (dark on white)
- Select correct language for local engine
Use Cases
- Digitize paper documents
- Extract data from receipts/invoices
- Make scanned PDFs searchable
- Accessibility for screen readers
- Translation preparation
FAQ
Recognizes handwriting?
AI engine: 70-85%. Local Tesseract: 40-60% (limited).
Preserves formatting?
No, OCR extracts text only. Use PDF-to-Word for layout preservation.