How text recognition works
This tool uses optical character recognition (OCR) to find letters in an image and turn them into editable text. Sharp, high-contrast images give the most accurate results.
What's actually happening behind the scenes
Our engine runs Tesseract, a well-established, widely-used open-source OCR engine, tuned specifically for English printed text. It analyzes your image, identifies individual characters and words by their shapes, and reconstructs them as real, editable text - this is genuine character recognition, not a simple image description, which is why results depend heavily on how clearly the original text was printed, photographed, and lit.
Getting better results
Use a sharp photo taken straight on, avoid shadows and glare, and crop to the text you need. Handwriting and unusual fonts are less accurate.
Why printed text works so much better than handwriting
OCR engines are built around recognizing the consistent, standardized letterforms of printed fonts - every lowercase "a" in a given printed font looks essentially identical, which is exactly the kind of predictable pattern character recognition is good at matching. Handwriting breaks that assumption completely, since the same person's handwritten letters vary from word to word, and different people's handwriting varies even more. This is why handwritten text remains a much harder, less reliable problem than recognizing printed text, even with modern OCR technology.
What you can use it for
- Copy text from a screenshot of a message, error or web page you cannot select.
- Turn a photo of a printed page, receipt, notice or business card into editable text.
- Pull quotes, addresses or reference numbers out of an image instead of retyping them.
Tips for the most accurate text
- Light and focus: photograph in good light and tap to focus on the text. Blurry or dark images lose letters.
- Straight on: hold the phone parallel to the page so lines are not slanted or curved.
- Crop first: remove photos, logos and background clutter so only the text area is left.
- Size matters: text should be clearly readable when you zoom in. Very small print in a large photo is hard to recognise.
Who actually needs this, and why
Students and researchers who photographed pages from a printed book and need the text in an editable, searchable format rather than retyping it by hand. Office workers who received an important notice only as a photo and need its content as text to forward, edit, or search. Anyone extracting text from a screenshot of an email, article, or chat message when copying directly from the original source isn't possible.
What happens with mixed content on a page
If your photographed image includes a mix of actual text alongside tables, diagrams, or logos, the OCR engine extracts just the readable text content and effectively ignores the non-text visual elements, since character recognition isn't designed to interpret or reproduce those. A page with an embedded table might have its text extracted correctly but without the original grid structure or column alignment preserved.
Checking your result
OCR is remarkably accurate on clean printed text, but it's never guaranteed to be perfect - it's worth a quick proofread of the extracted text, paying particular attention to numbers, proper names, and unusual words, since those are exactly the places a misread character is most likely to slip through unnoticed and most likely to matter if it does.
Working with a whole document?
For a multi-page scan, use our OCR PDF tool instead - it turns a scanned PDF into a searchable, copyable PDF in one go, rather than extracting plain text from a single image.
Privacy
Your image is processed on our servers over an encrypted connection and deleted automatically once the text has been read. There's no account required and no email collected at any step.
Why image quality matters so much for accuracy
Character recognition works by analyzing the precise shape of each letter, so anything that distorts those shapes - blur from camera shake, uneven lighting that washes out part of the text, a skewed angle that stretches letters unevenly - directly reduces how accurately the engine can identify what it's looking at. A sharp, flat, evenly-lit photo of clean printed text routinely produces near-perfect results; a blurry, shadowed, or heavily angled photo of the same text can introduce a meaningful number of character errors, simply because the underlying shapes become genuinely ambiguous to the recognition engine.
Extracting text from a screenshot specifically
Screenshots tend to produce excellent OCR results, since the text is typically rendered at consistent, clean resolution with no camera-related distortion at all - no blur, no angle, no uneven lighting. This makes screenshot-to-text one of the most reliable use cases for this tool, which is why it's commonly used to pull text out of an error message, a chat conversation, or a webpage that doesn't allow normal text selection.
Business cards and short text snippets
This tool works just as well on short pieces of text as on full pages - a photographed business card or a product label goes through the same recognition process as a full page of text. For very short text snippets, it's especially worth a quick proofread afterward, since a single misread character stands out more and matters more in a short string like a phone number than it would buried within a longer paragraph.
What happens to formatting after extraction
The extracted text comes back as plain text, with line breaks generally following the original layout but without fonts, colors, or other visual formatting carried over - this tool focuses specifically on getting the words right rather than reproducing a page's visual design. If you need the extracted text formatted into a proper document afterward, pasting it into a word processor and applying whatever formatting the content actually needs there is the natural next step once the genuinely hard part - reading the text correctly in the first place - has already been taken care of for you automatically, start to finish, in just the few seconds it takes to process the image.