Text Scanner — Extract Text from an Image

This text scanner online is powered by Tesseract.js, one of the most widely used text recognition engines. It supports 15 languages including English, Ukrainian, Russian, German, French, Spanish, Italian, Portuguese, Polish, Dutch, Japanese, Chinese (Simplified), Korean, and Arabic — covering Latin, Cyrillic, CJK, and Arabic scripts. Upload any photo to scan text from image files instantly — all processing runs entirely in your browser, so no images or extracted text leave your device. This makes it a safe image to text tool for sensitive content like personal documents, business cards, and confidential notes. Language selection improves accuracy for non-English text by loading the appropriate character recognition model. The extracted text is presented in a copyable format, ready to paste into any editor, spreadsheet, or messaging app.

Use it to extract text from photo captures of printed pages, business cards, street signs, restaurant menus, labels, whiteboards, book pages, handwritten notes (with variable accuracy), and any image containing readable characters. The photo to text conversion works with screenshots, scanned pages, and camera photos — use the Screenshot Scanner to verify the source type before extraction. Scans multiple text blocks within a single image, preserving line breaks in the output. For best results with handwriting, use clear block letters rather than cursive.

The Text Scanner is optimized to scan text from any picture quickly — photos of signs, screenshots, labels, and casual captures where you just need the words extracted. The Document Scanner is designed for structured documents like contracts, letters, and forms where preserving layout matters. For receipt-specific extraction with price and item parsing, use the Receipt Scanner. Pick the tool that matches your source material for optimal accuracy.

When scanning text, use high-resolution images — more pixels give the OCR engine more data to work with. Ensure good contrast between text and background: dark text on light backgrounds produces the best results. Avoid shadows, reflections, and motion blur across the text area. If accuracy is low, try cropping to focus on smaller sections of text. Selecting the correct language before scanning significantly improves recognition for non-Latin scripts.