Image to Text (OCR)

We use Tesseract.js, an open-source OCR (Optical Character Recognition) engine that runs entirely in your browser. It analyzes the image pixels to recognize letters, words, and paragraphs.

Choose from 20+ popular languages in the dropdown, including Chinese, Japanese, Korean, Arabic, Hindi, and major European languages. Tesseract.js supports 100+ languages total. Language data is downloaded on first use (~2-15MB per language).

No. OCR processing happens locally in your browser using WebAssembly. Images are not uploaded to our servers during extraction.

JPEG, PNG, WebP, BMP, and TIFF. OCR usually works better with high-contrast images and clear text. Around 300 DPI is a practical target for scanned documents.

Accuracy depends on image quality. Clean, high-resolution images with standard fonts typically achieve 95%+ accuracy. Handwriting, low resolution, or unusual fonts may reduce accuracy.

Tesseract.js is trained primarily on printed text. Handwriting recognition is limited and results are often poor — especially cursive. For handwriting, a dedicated service like Google Vision API will perform significantly better.

Yes. You can upload multiple images in one go. The tool processes them in sequence and outputs all extracted text in a single result, with each image's text clearly labeled. You can then copy the combined text or download it as a .txt file.

The first time you select a new language, Tesseract.js downloads the corresponding language data file (typically 2-15MB per language, cached after the first use). English is always pre-loaded and requires no extra download. Processing time varies by language complexity.

The OCR engine and selected language data are downloaded on first use and cached in your browser. Subsequent runs in the same session are significantly faster. The progress bar and status text show what is happening during initialization.

Yes. Tesseract.js runs via WebAssembly in all modern mobile browsers. You can photograph a document with your phone camera and extract text immediately. Processing is slower than desktop but fully functional.

Google Lens and Adobe Scan typically use cloud-based processing. Our OCR runs in the browser, so image files are not uploaded to our servers during extraction. That browser-local workflow can be useful for sensitive documents such as contracts, medical records, or financial statements.

This tool handles images only. For PDF text extraction, use our <a href="/pdf-to-word">PDF to Word converter</a>. If your PDF contains scanned pages (image-based), export each page as an image first, then run OCR here.

Aim for around 300 DPI for scanned documents. Higher resolution can help, especially for small text. If your scan is low-res, try upscaling it first with our <a href="/image-upscaler">AI Image Upscaler</a> before running OCR.

Yes. Screenshots of websites, chat messages, code editors, and apps work well because they contain clean, high-contrast text. The tool handles multi-column layouts and mixed content.