Extract Text From an Image (OCR)

What affects OCR accuracy

This tool currently recognizes English text only. Within that, accuracy depends heavily on the source image: printed text in good lighting with reasonable resolution and contrast will extract cleanly, while handwriting, heavy glare, low resolution, or skewed angles will reduce accuracy — the same limitations any OCR technology runs into, not something unique to running it in a browser.

Because recognition runs on your own device rather than a server, a large or high-resolution image will take longer to process than it would on a cloud service — that's the real trade-off for not uploading your photo anywhere. If you're scanning a document specifically to convert it to a PDF, pairing this with the PDF Scanner tool first (for a cleaner, cropped, contrast-corrected source image) will generally improve OCR accuracy.

What this tool actually does — and doesn't do

This tool reads text out of an image using Tesseract.js, an OCR engine that runs entirely in your browser — the image is never uploaded, and recognition happens on your own device.

Accuracy depends heavily on the source: sharp, straight, high-contrast printed text will convert almost perfectly, while handwriting, low-resolution photos, or tilted scans produce more errors. That's not a limitation of the tool, it's the nature of OCR — the engine can only read what the pixels clearly show.

If a scan comes out garbled, re-shoot it with even lighting and the text flat against the camera, or run the image through the Image Compressor's contrast-friendly settings first. The extracted text downloads as a plain .txt file ready to paste anywhere.

How to extract text with OCR, step by step

1. Add a photo or scan. Sharply lit, straight-on shots of documents, receipts, or screenshots work best.
2. Wait for recognition. The OCR engine runs entirely on your device — a progress indicator shows it working, and the extracted text appears in an editable panel.
3. Review and correct. Read the result against the preview beside it; fix stray characters before copying or downloading as .txt.

Limits worth knowing

OCR accuracy depends on image quality: crisp text is read almost perfectly, while blurred, skewed, or low-light photos produce more errors — the honest response is to retake the shot, not to hide the mistakes. Handwriting is recognized only when neat and consistent. The engine recognizes Latin-script languages best.

Privacy

The recognition model is loaded into your browser and runs on your device. Your images and text never leave it.