To run optical character recognition on screenshots or scanned documents privately, use the local OCR Extractor tool. By compiling Tesseract.js inside your browser RAM, it performs image-to-text scanning entirely on your local machine.
Whether you are copying billing text from an invoice photo, saving code lines from a video tutorial frame, or scanning receipts, Optical Character Recognition (OCR) is indispensable. In our agency's day-to-day operations, we handle hundreds of document scans, and we advocate utilizing client-side local OCR to preserve data privacy.
Modern In-Browser OCR Technology
Previously, OCR required large desktop software installations or expensive server APIs. Modern web runtimes allow library models (like Tesseract.js WebAssembly) to run directly inside your browser. This enables you to drop an image of a private invoice or contract, scan it, and copy the text offline, keeping your private receipts completely safe.
Instructions for Offline OCR Scanning
- Launch the Local OCR Extractor.
- Drag and drop your image (JPG, PNG, WebP) into the upload container.
- Select the target language (English, Spanish, etc.).
- Click Extract Text. The browser runs character scanning locally and prints the editable text on your screen in seconds.
Frequently Asked Questions
Which image formats are supported by local OCR?
Our local OCR tool supports common image formats including JPG, PNG, WebP, and BMP. You can also paste screenshots directly from your clipboard.
How is local OCR kept private?
It uses Tesseract.js compiled to WebAssembly. The entire OCR engine loads inside your browser and processes the image locally. No image data is transmitted over the internet.
Does it support languages other than English?
Yes. The underlying local engine can download language-specific trained data packs to parse Spanish, French, German, Chinese, and many other scripts.
Why does the OCR sometimes misread text?
OCR accuracy depends heavily on image contrast, font size, and resolution. For best results, use high-resolution, unblurred images with dark text on a light background.