PDF to text with OCR — in your browser, no uploads

Two kinds of PDFs

Before you reach for OCR, it helps to know which kind of PDF you have. A text PDF already has real characters embedded in it — you can select a word with your cursor and copy it. A scanned PDF is really a stack of images: a photo or scanner output wrapped in a PDF container. Selecting text does nothing, because there is no text — just pixels that look like letters.

For text PDFs, you don't need OCR at all. Our PDF Text Extractor pulls the embedded text directly and instantly. For scanned PDFs, you need Optical Character Recognition to turn those pixels back into characters.

Why do OCR in the browser?

Most "pdf to text" converters online work by uploading your file to a server, running OCR there, and sending the text back. That is fine for a public brochure — but it is a terrible fit for contracts, medical records, ID documents, invoices, or anything with a client's name on it. Once your document lands on a stranger's server, you have to trust their retention policy, their staff, and their security.

Browser-based OCR flips that model:

• Nothing is uploaded. The PDF stays in the tab's memory. No network request carries your document off your device.
• Works offline. After the OCR engine loads once, you can disconnect the network and it still runs.
• No accounts, no queues. No email sign-up, no captcha, no "we'll send your result in 5 minutes".
• Free within your device's limits. The only cost is the CPU cycles you already own.

How browser OCR actually works

The stack is simpler than it looks. A JavaScript PDF renderer such as PDF.js turns each page of your PDF into a bitmap on an HTML canvas. That bitmap is then handed to an OCR engine — typically Tesseract.js, a WebAssembly build of the same Tesseract project Google has maintained for years. Tesseract analyzes the pixels, segments lines and words, and outputs Unicode text plus confidence scores.

Roughly, the pipeline is:

1. Load the PDF into memory with PDF.js.
2. Render each page to a canvas at ~200–300 DPI.
3. Send the canvas to Tesseract.js, wait for text.
4. Concatenate pages, download as .txt or searchable PDF.

Getting the best OCR accuracy

• Scan at 300 DPI. Below 200 DPI, letter shapes break down and error rates climb fast.
• Prefer grayscale or black-and-white originals. If your source is a photo, straighten it and crop to the page.
• Pick the right language. Tesseract has hundreds of language packs — using the correct one dramatically improves both accuracy and character set.
• Trim noise. Coffee stains, staple holes, and handwritten notes in the margins all hurt recognition. Cropping helps.

Common use cases

• Turning a scanned contract into searchable text before signing.
• Copying quotes out of a scanned book chapter or PDF slide deck.
• Extracting invoice line items from scanned receipts for bookkeeping.
• Making a legacy archive of scanned PDFs full-text searchable.
• Pulling addresses, phone numbers, or IDs out of forms without sending them to a third party.

Limits to be aware of

Browser OCR is powerful, but it isn't magic. Handwriting recognition is still weak in Tesseract. Very long documents (hundreds of pages) will be slower than a server with a GPU. And if a scan is genuinely unreadable to a human eye, no engine will save it. For 95% of everyday "pdf to text" jobs — clear typed pages in a mainstream language — it works beautifully.

Try it now

If your PDF already has embedded text, use the PDF Text Extractor for an instant result. A dedicated browser OCR tool for scanned PDFs is on the tools roadmap — same principle, same privacy guarantee: your documents never leave your device.

FAQ

What is OCR and why do I need it for a PDF?

OCR — Optical Character Recognition — reads pixels of text in a scanned image or PDF and turns them into selectable, searchable characters. If your PDF was made by a scanner or a phone camera, the text inside is really just an image. OCR is what turns it back into real text you can copy, search, and edit.

Can OCR really run entirely in the browser?

Yes. Modern OCR engines like Tesseract.js compile to WebAssembly and run inside your browser tab. Your PDF is never uploaded — pages are rendered to a canvas and recognized locally on your device.

Is it as accurate as cloud OCR services?

For clean, high-resolution scans in common languages, local OCR is usually within a few percent of cloud accuracy. Poor scans, handwriting, or unusual scripts still favor larger cloud models — but for typical documents, browser OCR is more than enough.

Do I need to install anything?

No. Everything runs in a normal browser tab — no installs, no plugins, no accounts.