Extract readable text from images using OCR technology. Upload an image, scan printed text, and copy the extracted content instantly - fully client-side and privacy-friendly.
OCR solves a specific problem: text that's visually present in an image but not selectable as real characters. A screenshot of an article, a photo of a printed page, a scanned receipt, or a slide exported as an image all lock their text inside pixels - you can't select, search, or copy it directly.
This tool runs Tesseract.js, an open-source OCR engine, against your uploaded image entirely in the browser, so the image itself never leaves your device - a real advantage for receipts, forms, or other sensitive material. The extracted text appears in a read-only result box with a one-click Copy button - there's no in-tool editor and no file-download option, so plan to paste the result into whatever document or spreadsheet you're building.
This OCR (optical character recognition) tool extracts machine-printed or typed text from an uploaded image - screenshots, scanned documents, receipts, or photos of printed pages - and turns it into plain text you can copy out and reuse elsewhere. Recognition runs on Tesseract.js directly in your browser: your image is handed straight to the OCR engine locally and is never uploaded to a server. The engine currently recognizes English text only, and like all Tesseract-based OCR, it's built for machine-printed and typed text - handwriting recognition is unreliable and not a supported use case.
Upload an image containing printed text such as documents, screenshots, or photos.
The OCR engine scans the image and extracts readable text automatically.
Review the extracted text for accuracy before copying it - the result is read-only in this tool.
Copy the extracted text to clipboard and use it anywhere instantly.
Upload a screenshot of an article, error message, or chat you can't select text from, then copy the extracted text out.
Photograph a printed receipt or invoice and extract the line-item text for expense tracking or bookkeeping - the image never leaves your browser.
Use the Image Cropper to cut out surrounding clutter and isolate just the text region before running OCR - less visual noise generally means more accurate recognition.
This tool has no HEIC decoding built in, so an iPhone photo saved as HEIC often won't preview or process correctly outside Safari - convert with HEIC to JPG first, then run OCR on the JPG.
Don't run an image through the Image Compressor before OCR - compression artifacts around text edges can reduce recognition accuracy. Use the original-quality image instead.
Best For
Source
error-screenshot.png - a screenshot containing an error messageResult
Plain text in a read-only result box, ready to copy with the Copy buttonRecognition runs via Tesseract.js locally in the browser at English-only accuracy. The result box is read-only - there's no in-tool editor, only Copy to Clipboard.
Extract text from a screenshot of an article, error message, or chat that you can't select directly.
Photograph a printed receipt and pull out the text for expense tracking, keeping the original receipt image private since nothing is uploaded.
Extract the printed text from a presentation slide or infographic that was exported or shared as a flat image.
Problem
Solution
Tesseract.js, the engine behind this tool, is built for machine-printed and typed text. Handwriting recognition is unreliable and will often produce garbled or incomplete results.
Problem
Solution
The result box is read-only - you can copy the text out with the Copy button, but you can't type corrections directly in the result area. Paste it into a text editor or document to fix recognition errors.
Problem
Solution
This tool has no HEIC decoding built in, so a HEIC file often won't preview or process correctly outside Safari. Convert to JPG first with HEIC to JPG.
Problem
Solution
The recognition language is currently fixed to English - there's no language selector, so text in other languages or non-Latin scripts won't be recognized accurately.
Sharp, evenly lit, high-contrast text recognizes far more accurately than blurry, low-resolution, or glare-heavy photos.
Use the Image Cropper to remove surrounding background or clutter before running OCR - isolating the text region tends to improve accuracy.
This tool is built for machine-printed and typed text. Handwritten notes, decorative fonts, and heavily stylized text are much less reliable.
OCR is not perfect - always review the extracted text against the source image before using it somewhere accuracy matters, like a contract or receipt total.
The OCR engine is currently set to English - there's no language selector, so other languages and non-Latin scripts won't be recognized accurately.
Tesseract.js, the OCR engine used here, is designed for machine-printed and typed text. Handwriting recognition is unreliable and not a supported use case.
The extracted text appears in a read-only box with a Copy to Clipboard button only - there's no way to edit the text in place or download it as a file.
The Extract Text button shows a static "Extracting..." label with no percentage or progress bar while OCR runs, which can take several seconds on larger images.
Your image is never uploaded, but the browser does fetch the OCR engine's worker script, WASM core, and English language data from a CDN the first time you use it - a fully offline environment will fail to load these.
This page processes a single image per run - there's no batch or bulk OCR option.
This tool's accuracy depends heavily on whether the source text is machine-printed/typed or handwritten.
| Printed or Typed Text | Handwritten Text | |
|---|---|---|
| Recognition engine fit | Tesseract.js is trained and built for this - the intended use case | Not a supported use case - Tesseract-based engines aren't designed for handwriting |
| Typical accuracy | Generally reliable on clear, well-lit source images | Unreliable - expect missing words, garbled characters, or empty results |
| Good source examples | Screenshots, scanned documents, printed receipts, slides | Handwritten notes, whiteboard writing, signatures |
Which should you use?
Use this tool for printed or typed text sources. For handwritten content, this tool is unlikely to produce a usable result - there's no dedicated handwriting recognition mode.
OCR visitors often have privacy concerns - they are dealing with scanned documents, receipts, or photos that contain sensitive information. The page works best when it prominently confirms that processing happens in the browser and no image data is sent to any server.
No. Text recognition runs in your browser using Tesseract.js, and your image is handed directly to the OCR engine locally - it's never uploaded anywhere. The browser does fetch the OCR engine's own script and English language data from a CDN the first time you use it, but that's the engine loading itself, not your image being sent out.
Not yet - the result appears in a read-only box with a Copy to Clipboard button. To fix recognition errors, copy the text out and edit it in a text editor or document.
Not currently. Recognition is set to English only, and there's no language selector in the interface.
Not reliably. Tesseract.js, the OCR engine behind this tool, is built for machine-printed and typed text. Handwriting recognition is a different problem this tool doesn't target, so results on handwritten notes are often garbled or incomplete.
Not currently - the only output option is the Copy to Clipboard button. Paste the copied text into a document or note-taking app to save it.
The upload step rejects anything that isn't an image file. If a valid image fails to produce text, common causes are low resolution, heavy blur or glare, handwritten content, a HEIC photo the browser can't decode, or a genuinely blank/text-free image - try a clearer, higher-resolution, printed-text image.
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