Image to Text OCR
Extract editable text from images with private browser-based OCR, language support, live progress, and instant copy or TXT download.
OCR Settings
Image Preview
How it works
Modern browser OCR tools commonly let users upload screenshots, scanned pages, receipts, and photos, choose a recognition language, watch live progress, and then copy or download editable extracted text. Many privacy-focused tools run OCR fully inside the browser with Tesseract.js or WebAssembly-based engines so images do not need to be uploaded to a server.
- Drag-and-drop image upload is a common OCR workflow feature.
- Editable text output with copy and TXT download is standard in browser-based OCR tools.
- Language selection improves recognition accuracy for multilingual OCR.
- All processing happens locally in your browser - your images are never uploaded.
Frequently Asked Questions
OCR (Optical Character Recognition) is a technology that converts images containing text into machine-readable text. It works by analyzing the shapes of characters in an image and matching them to known characters using pattern recognition and machine learning algorithms.
Yes, this OCR tool is completely free to use. All processing happens locally in your browser using Tesseract.js, so there are no hidden costs or limitations on the number of images you can process.
This tool supports JPG, PNG, WebP, BMP, TIFF, and HEIC/HEIF image formats. Most common image formats used for scanning documents and photos are compatible.
Yes, your data is completely safe. All image processing is done locally in your browser using Tesseract.js. Your images are never uploaded to any server, making this a fully private and secure OCR solution.
This tool supports over 20 languages including English, Hindi, Spanish, French, German, Italian, Portuguese, Dutch, Turkish, Polish, Romanian, Czech, Hungarian, Swedish, Greek, Russian, Arabic, Japanese, Korean, Chinese (Simplified & Traditional), Vietnamese, Thai, and Indonesian.
The accuracy depends on image quality, text clarity, and font type. The tool uses Tesseract.js with preprocessing steps like grayscale conversion, contrast enhancement, and binarization to improve recognition. Clear, high-contrast images with standard fonts produce the best results.