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Free Image to Text (OCR)

Extract text from any image

Upload or paste an image and instantly extract all text from it using Tesseract.js, the most popular open-source OCR engine with over 38,000 GitHub stars. Supports 100+ languages including English, Arabic, Chinese, Japanese, Korean, Hindi, and more. All processing happens locally in your browser — no signup, no server, no API calls. Your images stay on your device.

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Engine:Tesseract OCR

Preparing OCR interface...

What Is Tesseract.js and How Does This OCR Tool Work?

This image-to-text tool is powered by Tesseract.js, the most popular open-source OCR library for the web with over 38,000 GitHub stars. Tesseract.js is a JavaScript port of the Tesseract OCR engine, originally developed at Hewlett-Packard Labs in the 1980s and later maintained and improved by Google. It can extract text from images in over 100 languages, including English, Arabic, Chinese, Japanese, Korean, Hindi, Russian, and many more.

The engine runs entirely in your browser via WebAssembly — no server, no cloud processing, no API keys. You upload or paste an image, select the language, and the OCR engine analyzes pixel patterns to recognize characters and words. It works with JPG, PNG, BMP, WEBP, and GIF formats, and handles screenshots, photos of documents, receipts, signs, whiteboards, and scanned pages.

Tesseract.js v7 brings significant improvements over earlier versions: 54% smaller language files for English, 73% smaller for Chinese, approximately 50% faster initial load times, reduced runtime memory usage, and fixed memory leaks that affected long-running applications. The result is a fast, reliable OCR tool that runs on any modern device.

For Developers: Integrate Tesseract.js OCR in Your Applications

Tesseract.js is available on npm and supports both browser and Node.js environments. The API is straightforward — create a worker with createWorker(), then call worker.recognize(image) to extract text. For high-throughput applications, the Scheduler pattern allows you to distribute OCR jobs across multiple workers for parallel processing, making it practical for batch document scanning or real-time video text extraction.

The library works with webpack, ESM imports, and CDN script tags. Language data files are loaded on demand from a CDN and cached locally, so only the languages you actually use are downloaded. Developers building document scanning apps, receipt processors, accessibility tools, or content extraction pipelines will find Tesseract.js a production-ready solution that eliminates the need for paid cloud OCR services. For PDF text extraction, the team recommends Scribe.js, a companion project built on the same OCR foundation.

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How It Works

1

Upload an image, paste from clipboard, or drag and drop.

2

Select the language and click Extract Text to run OCR locally.

3

Copy the extracted text or download it as a file.

Key Features

Powered by Tesseract.js — the world's most popular open-source OCR engine (38K+ GitHub stars)
Supports 100+ languages including English, Arabic, Chinese, Japanese, Korean, and Hindi
Upload images or paste from clipboard (Ctrl+V / Cmd+V)
Supports JPG, PNG, BMP, WEBP, and GIF formats
Runs entirely in your browser via WebAssembly
No signup or account required
No server or API calls
Private by design — images never leave your device

Privacy & Trust

Images are processed locally in your browser
No images are uploaded or stored anywhere
No tracking of image content
Built using open-source Tesseract.js OCR technology

Use Cases

1Extract text from screenshots or photos
2Digitize printed documents and receipts
3Copy text from images that can't be selected
4Convert scanned PDFs or book pages to editable text
5Extract text from memes, banners, or signs
6Read text from photos of whiteboards or handwritten notes
7Accessibility — make image text readable by screen readers
8Grab text from slides or presentation screenshots

Frequently Asked Questions

Limitations

  • Accuracy depends on image quality and clarity
  • Handwritten text recognition is limited
  • Very large images may be slow on older devices
  • Complex layouts (tables, multi-column) may not preserve formatting
  • Initial language data download may take a few seconds on first use
  • Does not support PDF files directly