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or click to browse — JPG, PNG, WebP, PDF supported

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About This Tool

How to Extract Text from an Image (OCR)

  1. 1Drop or select an image containing text — photos of documents, screenshots, scanned pages, signs, or whiteboards all work well.
  2. 2The OCR engine processes the image in your browser and extracts all detected text, preserving line breaks and structure where possible.
  3. 3Review the extracted text. OCR accuracy is highest on printed text with clear contrast; handwriting and stylized fonts may need manual correction.
  4. 4Copy the text directly or download it as a .txt file. Nothing is uploaded — all processing runs locally.

When to Use Image OCR

Digitizing Scanned Documents
Convert scanned contracts, receipts, letters, and forms into editable, searchable text without retyping. Particularly useful for archiving older paper documents.
Extracting Text from Screenshots
Pull text from app screenshots, error messages, social media posts, or any other image where the text isn't selectable. Faster and more accurate than manual transcription.
Translation Workflows
Extract text from images in foreign languages before pasting into a translation tool — far faster than typing out unfamiliar characters manually.
Data Extraction
Pull numbers, names, or structured data from tables, charts, or forms captured as images — useful for importing data into spreadsheets without manual entry.

Why Use Browser-Based OCR

Documents sent through cloud OCR services are processed on remote servers — a significant concern for contracts, financial records, medical documents, and other sensitive files. This tool runs the OCR engine locally in your browser using Tesseract.js, so your documents never leave your device. For the reverse operation — adding text to an image rather than extracting it — our Add Text to Image tool handles that in the same browser-based workflow. If you're working with PDF documents and need to extract text from scanned pages, also explore the OCR tools available at PDFToolShack.

Frequently Asked Questions

No — never. All OCR processing happens entirely inside your browser using Tesseract.js and PDF.js, both open-source JavaScript libraries. Your file never leaves your device, and no data is sent to any server. This means your documents, photos, and their contents stay completely private.

You can upload JPG, PNG, and WebP images, as well as PDF files (including multi-page PDFs). For PDFs, each page is rendered individually and then processed for text. You can view individual page thumbnails and the extracted text from all pages is combined into one output.

Accuracy depends heavily on image quality. For clear, high-resolution documents with standard fonts, accuracy is typically 95–99%. Results are lower for handwriting, decorative fonts, low-resolution scans, or images with complex backgrounds. The confidence indicator shown after processing gives you a rough guide to result quality. For best results, use high-resolution, well-lit images with dark text on a light background.

This tool uses Tesseract OCR, which is optimised for printed text rather than handwriting. Neat, block-capital handwriting may produce reasonable results, but cursive or irregular handwriting will typically be inaccurate. For handwriting recognition, a dedicated AI-powered tool would give better results.

The first time you use this tool in a browser session, Tesseract.js downloads the OCR language model file for your selected language (typically 2–10 MB depending on language). This is cached by your browser, so subsequent runs in the same session are much faster. The download only happens once per language per session.

Yes — use the Language dropdown that appears after your first OCR run, then click “Re-run OCR” to process the same file with the new language model. This is useful if a document contains mixed-language content or if the initial language setting was wrong.