What is scan text from image?
Scan text from image — also called OCR (Optical Character Recognition) — is the technology that reads the visual shapes of letters and numbers in an image and converts them into machine-readable, editable text. Our free image to text converter runs this process entirely inside your browser, without sending your images to any external server.
Whether you need a quick photo to text converter for a single screenshot or a reliable JPG to text tool for regular document digitisation, this tool handles it all. Upload any image — a photograph, screenshot, scan, or camera shot — and extract the text in seconds.
How to use this photo to text converter
1
Upload your image
Drag and drop any image file, or click to browse. JPG, PNG, WebP, BMP, GIF, and TIFF are all supported.
2
Choose output format
Select plain text, Markdown for structured documents, or clean line format for lists and tables.
3
Click 'Get text from image'
The OCR engine analyses your image locally and extracts all readable text.
4
Copy or download
Edit the result if needed, then copy to clipboard or download as a .txt file.
Common uses for image to text conversion
Extract text from scanned documents
Convert scanned PDFs or paper documents into editable digital text. Perfect for archiving physical documents, extracting information from old records, or digitising printed forms.
Get text from screenshots
Extract text from screenshots of websites, apps, error messages, or any on-screen content. Useful when you can't select and copy text directly from the source.
Read text from photos of signs
Capture and extract text from photos of road signs, menus, business cards, whiteboards, or presentation slides taken with your camera.
Convert book pages to text
Photograph pages from books, magazines, or printed articles and convert them to searchable, copyable digital text using this photo to text converter.
Extract data from receipts and invoices
Pull text from photos of receipts, invoices, or bills for expense tracking, accounting, or record-keeping purposes.
Digitise handwritten notes
Convert photos of handwritten notes, letters, or notebooks into digital text — useful for organising notes taken during meetings, classes, or personal journaling.
Getting the best results from JPG to text extraction
The quality of text extraction from any image to text converter depends directly on the quality of the source image. OCR engines read text by analysing visual contrast, letter shapes, and spacing. Here are the most important factors for accurate extraction:
Image resolution
Higher resolution means more pixel data per character, giving the OCR engine more information to work with. For scanned documents, 300 DPI (dots per inch) is the standard recommended minimum — 600 DPI is better for small text. For photos taken with a phone camera, make sure to photograph from close enough that text fills a significant portion of the frame.
Contrast and lighting
Black text on a white background is the easiest scenario for any photo to text converter. Coloured text, text on textured backgrounds, or low-contrast combinations (grey text on white, yellow on cream) significantly reduce accuracy. When photographing documents, use even lighting — flash reflections, shadows, and hot spots all introduce noise that confuses the OCR engine.
Image straightness
Even a 5–10 degree rotation can noticeably reduce OCR accuracy. Most OCR engines have some tolerance for skew, but straightening the image first always produces better results. If your image is rotated, use your device's photo editor to straighten it before uploading to get text from image more accurately.
Font and text type
Clear, standard printed fonts produce the most reliable results. Decorative, script, or heavily stylised fonts are harder to recognise. Handwritten text is the most challenging scenario for any image to text converter — accuracy varies greatly depending on how neat and consistent the handwriting is. Printed block capitals are the easiest handwriting style for OCR engines to read.
Privacy — why local OCR matters
Many online OCR tools upload your images to a server for processing. This means your documents, photos, and any sensitive information they contain are transmitted over the internet and may be stored, processed, or accessed by the service provider. For documents containing personal data, financial information, medical records, confidential business documents, or private communications, this represents a real privacy risk.
This tool is different. The OCR engine — powered by Tesseract.js and compiled to WebAssembly — runs entirely inside your browser. Your images are processed on your own device, never transmitted anywhere. There is no server receiving your uploads, no storage, and no logging. It is genuinely private by design, not just by policy.
Frequently asked questions
How does the scan text from image tool work?+
This tool uses Tesseract.js, a JavaScript port of the industry-standard Tesseract OCR (Optical Character Recognition) engine originally developed at HP Labs and now maintained by Google. When you upload an image, the OCR engine analyses pixel patterns and identifies characters by comparing them against trained language models. Everything runs directly in your browser — no image data is ever sent to a server. The result is extracted text you can copy, edit, or download.
What image formats does the photo to text converter support?+
The image to text converter supports all common image formats including JPG/JPEG, PNG, WebP, BMP, GIF, and TIFF. For best results, use high-resolution images with clear, high-contrast text. Blurry, low-resolution, or heavily compressed images (like small thumbnails) will produce less accurate results. If you have a scanned PDF, convert it to an image first using any PDF viewer's screenshot feature or a PDF-to-image converter.
How accurate is the JPG to text extraction?+
Accuracy depends heavily on the quality of the source image. For clean, printed text on a contrasting background (like a typed document, book page, or printed sign), accuracy is typically very high — often 95–99%. Accuracy decreases for handwritten text, stylised fonts, text on complex backgrounds, very small text, or images with glare and shadows. To improve accuracy: use the highest resolution image available, ensure good lighting, avoid heavy rotation, and crop to the text area if possible.
Is it safe to use? Does my image get uploaded anywhere?+
Yes, it is completely safe. This tool runs 100% locally in your browser using WebAssembly — the OCR engine executes entirely on your device. Your images are never uploaded to any server, never stored anywhere outside your browser session, and never seen by anyone else. This makes it safe to use with sensitive documents, confidential files, personal photos, and private correspondence. When you close the browser tab, everything is gone.
Can I get text from image files with multiple columns or complex layouts?+
Yes. The OCR engine handles multi-column layouts, though with complex formatting, the order of extracted text may follow a left-to-right, top-to-bottom reading pattern rather than perfectly preserving the visual column structure. For structured documents, use the 'Markdown' output format which attempts to preserve headings and list structures. For tables and forms, the 'Lines' format often gives the cleanest output for copying into a spreadsheet.
What languages does the image to text converter support?+
The default language model is English (trained on the English alphabet and common words). Tesseract.js supports over 100 languages, but loading multiple language packs increases the download size. The current tool is optimised for English text. For other languages, the tool may still work for languages that share the Latin alphabet (French, Spanish, German, etc.), though accuracy may be lower than with a dedicated language model.
How can I get better text extraction results?+
Several techniques improve OCR accuracy significantly. Use a high-resolution image — at least 300 DPI (dots per inch) for scanned documents. Ensure good contrast between text and background (black text on white is ideal). Straighten the image before uploading — even a few degrees of rotation can reduce accuracy. Crop tightly to the text area to reduce noise. Avoid images with heavy JPEG compression artefacts. If working from a physical document, ensure even lighting without glare or shadows.
What is the difference between the output format options?+
Plain text extracts all recognised characters exactly as they appear, with original line breaks preserved. This is best for simple documents, single paragraphs, or when you want to process the text further. Markdown format attempts to detect structural elements — lines that appear to be headings are formatted with ## prefixes, and list-like lines get bullet point formatting. This is useful for structured documents like articles or reports. Lines format removes blank lines and ensures each non-empty line is preserved separately — useful for addresses, lists, and tabular data.
About this tool: Built with Tesseract.js, an open-source OCR engine. All processing is local — no image data leaves your device. Accuracy may vary based on image quality, font type, and language. This tool is intended for personal and commercial use under the standard terms of the Tesseract OCR library (Apache 2.0 licence).