Image Text Extractor
Process images in your browser — your files never leave your device.
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What is the Image Text Extractor?
This image text extractor pulls the text out of a screenshot, photo or picture and turns it into text you can copy, search or edit — no retyping. Drop in a screenshot of a tweet, a photo of a street sign, a picture of a printed page, or a screen capture of an error message, and it reads the text using an OCR (optical character recognition) engine that runs entirely inside your browser. It works well on clear, horizontal, high-contrast text — the kind you get from a clean screenshot or a well-lit photo of printed material — and less well on handwriting, stylised fonts, or text at an odd angle.
The recognition engine is Tesseract.js, an open-source OCR library compiled to WebAssembly so it can run directly in your browser instead of on a server. The language model for whichever language you pick downloads once — a few megabytes — the first time you use it, then runs locally for every image after that. Your image itself is never uploaded anywhere: the download is one-way (the model comes to your browser), and the recognition happens on your device.
Why use a free image text extractor?
Works on screenshots, not just scanned documents
Built for the everyday case of a screenshot or a phone photo — a tweet you want to quote, an error message you need to search, a sign you photographed while travelling.
Your image is never uploaded
Recognition runs entirely in your browser using a WebAssembly OCR engine. The picture never leaves your device, which matters for screenshots containing personal information.
Copy or download the result instantly
Once text is extracted, copy it straight to your clipboard or download it as a plain text file — no extra steps.
Batch multiple images at once
Drop in several screenshots or photos together and process them in one run, each with its own result and confidence score.
13 languages supported
Beyond English, the recognition model supports Spanish, French, German, Portuguese, Italian, Dutch, Russian, Simplified Chinese, Japanese, Korean, Arabic and Hindi.
How do you use the Image Text Extractor?
- 1
Drop in your screenshot or photo
Drag and drop, or click to browse. JPG, PNG and most other common image formats work.
- 2
Choose the text language
Pick the language the text in the image is written in — this determines which recognition model downloads and is used for reading.
- 3
Extract the text
The recognition model downloads once (a few MB) if you have not used that language before, then the image is processed locally. A progress bar shows the recognition stages.
- 4
Copy or download the result
Review the extracted text against the image preview, then copy it to your clipboard or download it as a .txt file.
How accurate is it?
Each result comes with an estimated confidence percentage from the OCR engine itself, reflecting how certain it is about the characters it read — not an independently verified accuracy figure. Clear, horizontal, high-contrast printed text (a clean screenshot, a well-lit photo of a printed page) typically produces the highest confidence and the fewest errors.
- Screenshots of digital text (tweets, articles, chat messages, error dialogs) tend to work best, since the source text is already crisp and high-contrast.
- Photos taken at an angle, in low light, or with a busy background behind the text will produce more misread characters — try to photograph text straight-on with good lighting.
- Handwriting is unreliable. The recognition model is trained primarily on printed text, so cursive or handwritten notes will often produce garbled or incomplete results.
- Stylised fonts, heavy design overlays and text embedded in complex graphics (logos, stylised headlines) are also less reliable than plain printed or typed text.
- Always proofread extracted text before relying on it, especially for names, numbers and anything that needs to be exact — OCR errors often look plausible (e.g. "0" read as "O", "1" read as "l") and are easy to miss on a quick glance.
What should you know before using it?
How reliably OCR extracts text from different kinds of images:
| Source image type | Typical reliability |
|---|---|
| Screenshot of digital text | High — crisp, high-contrast text is what OCR engines handle best. |
| Photo of a printed page, straight-on, good light | High — close to a scanned document once cropped reasonably tight. |
| Photo of a sign or label, at an angle or in low light | Medium — recognisable but expect some misread characters, especially small text. |
| Photo of a whiteboard or handwritten note | Low — handwriting recognition is a known weak point; expect to correct the result manually. |
| Stylised fonts, logos, decorative headlines | Low — designed for visual impact, not character clarity, so recognition often fails or garbles. |
Which tools relate to the image text extractor?
The image text extractor is one of 31 image tools on this site. These are the ones most often used alongside it — either because they handle the next step in the same job, or because they answer a question this tool raises.
OCR Online
The same underlying OCR engine, oriented toward multi-page and multi-language document scanning rather than single screenshots — use it for scanned forms, book pages or invoices.
PDF to Text
If your source is already a PDF rather than an image, extract its text directly instead of converting to an image first — it is faster and more accurate for text-based PDFs.
Online Proofreader
OCR output can include misread characters — run the extracted text through a proofreader afterward to catch obvious typos before you use it.
Word Counter
Check the word count of extracted text once you have it, useful when pulling a passage from a photographed page.
When should you use a image text extractor?
Because the image text extractor runs entirely in your browser, it suits work you would not want to hand to a third-party server — client files, unpublished drafts, anything under an NDA. These are the situations people reach for it in most often.
Quoting a tweet or social post
Screenshot a post and extract the exact text instead of retyping it by hand, reducing the chance of a transcription error in a quote.
Copying text from an error message or dialog box
Pull the exact wording of an on-screen error to paste into a search engine or a support ticket, rather than retyping it and risking a typo that changes the search results.
Digitising a photographed sign, menu or label
Turn a travel photo of a sign or menu into searchable, translatable text.
Pulling text from a meme or infographic
Extract the caption text from an image-based post so you can quote, search or archive it as plain text.
Frequently asked questions
Does this tool upload my image to a server?
Why does it need to download something the first time I use it?
Can it read handwriting?
What image formats does it accept?
Why is the extracted text slightly wrong in places?
Can I extract text from multiple images at once?
What languages does it support?
Is the image text extractor safe to use?
This tool runs entirely inside your browser. Your text, files and settings are processed on your own device and are never uploaded to our servers — there is nothing for us to store, log or leak. You can confirm it yourself: open your browser DevTools, switch to the Network tab, and use the tool. You will not see an upload request. It also means the tool keeps working if your connection drops mid-task.
Where do these figures come from?
Every method, threshold and standard this page relies on, with a link to the document that defines it. Check them — a tool that will not show its sources is asking you to take its word for it.
- 1Tesseract.js — Pure JavaScript OCR for 100+ languages
Tesseract.js project documentation
Supports: The description of the OCR engine as an open-source, WebAssembly-compiled recognition library that runs locally in the browser.
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