What is OCR Text Extraction?
OCR (Optical Character Recognition) is a technology that converts images containing text into editable and searchable digital text. It analyzes the visual patterns of characters in an image and translates them into machine-readable text using advanced machine learning algorithms.
Our OCR tool uses Tesseract.js, a powerful open-source OCR engine that runs entirely in your browser. This means your documents never leave your device, ensuring complete privacy and security. It supports over 100 languages and can recognize text in various fonts, sizes, and styles.
100% Private
All processing happens in your browser - no uploads to servers
100+ Languages
Supports English, Spanish, Chinese, Arabic, and many more
Fast Processing
Extract text from images in seconds with real-time progress
High Accuracy
95%+ accuracy with clear images and standard fonts
Common use cases:
- Document digitization — Convert scanned documents and PDFs to editable text
- Receipt scanning — Extract text from receipts for expense tracking
- Screenshot text extraction — Copy text from screenshots and images
- Business card scanning — Extract contact information from business cards
- Note digitization — Convert handwritten or printed notes to digital text
- Translation preparation — Extract text from images to translate in other tools
For best results, use high-quality images with good contrast and lighting. Clear, straight text with standard fonts will provide the highest accuracy. The tool works with all common image formats including JPEG, PNG, WebP, and BMP.
Getting sharper OCR results
Tesseract, the engine behind this tool, was trained on characters roughly 20 to 30 pixels tall. A page scanned at 300 DPI renders 10 to 12 point body text at about that height, which is why 300 DPI is the practical floor for clean documents. Drop to 150 DPI and character strokes thin out to a few pixels, so an 8 and a B or an e and a c start to blur together. When you photograph text instead of scanning it, fill the frame with the page so the letters stay large.
Two more things move accuracy more than anything else. Skew: the layout analysis reads text row by row, so tilt the page more than about 5 degrees and whole lines get split or dropped. Straighten the image before extracting. Contrast: Tesseract converts your image to pure black and white using a single brightness threshold, so a grey receipt shot under a warm lamp can wash out entirely. Convert to grayscale and push the contrast up first, or shoot in even, indirect light.
This tool versus other OCR options
| OCR option | Cost | Runs offline | Image leaves device | Handwriting |
|---|---|---|---|---|
| This tool (Tesseract.js, in browser) | Free | Yes, in your browser | No | Weak |
| Google Cloud Vision | Free for first 1,000 images/month, then paid per 1,000 | No, cloud only | Yes, uploaded | Good |
| Adobe Acrobat OCR | Paid subscription | Yes, desktop app | No on desktop | Limited |
| Apple Live Text | Free on Apple devices | Yes, on device | No | Fair |
Character pairs that trip up OCR
Most mistakes are not random. They come from characters that share a shape once the image loses detail. When you proofread extracted text, scan for these first.
| Confused pair | Where it shows up | What helps |
|---|---|---|
| 0 and O | Serial numbers, codes | A slashed-zero font, or higher resolution |
| 1, l and I | Prices, part numbers | Serif fonts, which add distinguishing strokes |
| rn and m | Tight body text | More spacing between letters |
| 5 and S, 8 and B | Handwritten or low-DPI scans | Cleaner contrast and larger characters |
A worked example: an invoice screenshot
Say you drop in a screenshot of an invoice header. Run it once and the raw output might read:
- Invoice No: 1OO52-B
- Amount Due: $l,200.O0
Two errors, both predictable. The engine read the zeros in the invoice number as capital O, and it read the leading 1 in the amount as a lowercase l and one trailing 0 as O. Because the extracted text is editable right in the result box, you fix them to 10052-B and $1,200.00 in seconds. Re-scanning the same header at 300 DPI with the contrast raised usually clears both without any manual edits, which is the fastest way to avoid the correction step entirely.