What is OCR?
OCR (Optical Character Recognition) is technology that converts images containing text into machine-readable text. A camera or scanner captures an image, and OCR software analyzes the visual patterns to identify letters, words, and sentences.
How OCR works
- Preprocessing: Image is binarized (converted to black and white), deskewed (straightened), and noise-reduced
- Layout analysis: Identifies text regions, columns, and paragraphs
- Character recognition: Each character is compared against trained patterns
- Post-processing: Spell checking and context analysis improve accuracy
OCR accuracy factors
| Factor | Impact on accuracy |
|---|---|
| Image resolution | Higher DPI = better accuracy |
| Font clarity | Printed > handwritten |
| Lighting | Uniform lighting = better |
| Text orientation | Horizontal = best |
| Language | Training data coverage |
| Image noise | Less noise = better |
Best practices for high accuracy
Before taking/scanning the image
- Use 300+ DPI when scanning
- Ensure even lighting without shadows
- Keep text horizontal
- Use high contrast (dark text on white background)
Image types and expected accuracy
- Printed documents: 95–99% accuracy
- Screenshot of digital text: 95–99% accuracy
- Printed signs/labels: 85–95% accuracy
- Handwritten text: 60–80% accuracy (varies widely)
- Artistic/decorative fonts: 50–80% accuracy
Tesseract.js — browser-based OCR
Privatool's Image to Text tool uses Tesseract.js, an open-source OCR engine compiled to WebAssembly. This means:
- OCR runs entirely in your browser
- Images never uploaded to any server
- Works offline after first load (engine is cached)
- Supports 30+ languages
How to extract text from images free
- Go to Image to Text
- Upload image, drag and drop, or paste from clipboard (Ctrl+V)
- Select language
- Click "Extract Text"
- View confidence score and extracted text
- Copy text or download as
.txt