What is Image to Text (OCR)?
Image to Text (OCR) — An Image to Text (OCR) Tool is a free tool that extracts readable text from images, screenshots, and scanned documents using optical character recognition.
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Upload an image, run OCR, and copy editable text. Choose your OCR language and process directly in your browser.
Image to Text (OCR): Upload an image containing text (screenshot, photo, scan) and the tool extracts all readable text using OCR. Supports PNG, JPG, and WebP formats. Copy the extracted text or download it as a text file.
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Image to Text (OCR) — An Image to Text (OCR) Tool is a free tool that extracts readable text from images, screenshots, and scanned documents using optical character recognition.
Choose the OCR language that best matches the text in your image.
Upload a clear JPG, PNG, WebP, BMP, or other browser-supported image file.
Wait for the OCR engine to scan the image and generate editable text.
Review the output for spelling, line-break, or number-recognition errors.
Copy the extracted text or download it for use in documents, spreadsheets, notes, or translation tools.
If the result is weak, crop the image, increase contrast, or rerun with the correct language.
Copy text from screenshots into documents, emails, tickets, or notes
Extract receipt, invoice, and business-card text for bookkeeping or CRM entry
Turn scanned document photos into editable text snippets
Capture text from UI mockups, app screenshots, or website screenshots for product work
Extract printed notes, book passages, labels, forms, or signs for research
Prepare image text for translation, summarization, cleanup, or spreadsheet entry
Reduce manual typing in admin, student, research, and support workflows
OCR stands for optical character recognition. It scans an image, detects shapes that look like letters or numbers, and converts those shapes into editable text. OCR works best on printed text with clear contrast and predictable fonts, but it can also help with screenshots, scans, forms, receipts, and some handwriting.
OCR accuracy improves with sharp focus, high resolution, good lighting, horizontal text, and clear contrast between text and background. Low light, motion blur, perspective distortion, shadows, tiny fonts, decorative typefaces, watermarks, and compressed screenshots can reduce extraction quality.
Screenshots usually produce the cleanest output because the text is flat and high contrast. Photos of documents can work well if the camera is steady and the page is not angled. Scanned pages are strong input when the scan is not too compressed. For receipts and labels, crop out the background so the OCR engine focuses on the text area.
Choose the OCR language before processing whenever possible. The correct language helps the recognition engine interpret accents, symbols, character shapes, and word patterns. If an image mixes languages, run OCR once with the dominant language and rerun with another language if important text is missed.
Handwriting OCR is less reliable than printed text OCR because handwriting varies from person to person. Clear block letters work better than cursive. If a result contains mistakes, try cropping tighter, increasing contrast, rotating the image upright, or using a sharper photo before running OCR again.
The OCR workflow is designed for browser-based extraction and quick copy tasks. Always review the result before using it in invoices, legal documents, school work, medical notes, or financial records because OCR can misread similar characters such as O/0, I/1, S/5, and B/8.
Choose your OCR language before upload, or run OCR again after changing it.