OCR a Scanned PDF Privately, in Your Browser

How to Extract Text from a Scanned PDF

A scanned PDF is often a stack of page images. You can read it, but you cannot search it, copy from it, or paste a paragraph into an email. OCR (optical character recognition) reads those pixels and turns them into searchable text. GoPDFConverter performs that recognition in browser memory instead of sending the selected PDF to a conversion endpoint.

1. Open the OCR PDF tool and drop your file, or click Choose a PDF.
2. Pick the document language. English is the default; Spanish, French, German, Portuguese, and Italian are also available. Matching the language to your scan makes a big difference in accuracy.
3. Leave page orientation on auto for mixed or uncertain scans, or choose a fixed correction when every selected page has the same rotation.
4. Enter a page range like 1-3,5, or leave it blank to process every page.
5. Click Run OCR. The first run downloads the OCR engine and selected language data from a CDN; your browser can cache those dependencies.
6. Copy the extracted text, download .txt or .docx, or save a searchable PDF that keeps the original PDF pages and adds an invisible recognized-text layer.

The primary searchable-PDF path modifies the original document in place: page artwork, vectors, existing text, annotations, forms, metadata, bookmarks, and unselected pages remain, while selected pages receive an invisible coordinate-mapped text layer. If that structure-preserving save cannot complete safely, the tool identifies compatibility mode and asks you to check page quality and document features before sharing.

Why process OCR locally?

OCR is commonly used on identity documents, medical records, signed contracts, tax forms, and bank statements. Local recognition avoids sending those selected document bytes and recognized text to a separate OCR service for processing.

GoPDFConverter takes a different approach. The open-source Tesseract OCR engine is compiled to WebAssembly and runs directly on your device. Each page of your PDF is rendered to an image in browser memory, recognized there, and discarded. Network requests fetch the site code, PDF.js, Tesseract, the selected language data, and analytics; the PDF, page images, and recognized text are not sent away for processing.

Runtime depends on your hardware, scan complexity, browser state, and cache. In our controlled Chrome challenge, ten single-page runs took 2.19 to 3.99 seconds each after dependencies were cached. Treat that as one observed range, not a promise for another device or document.

Common OCR Use Cases

• Digitize family papers: turn scans of old letters, recipes, and journals into text you can search and preserve.
• Quote from a scanned book: extract a passage from a photographed or scanned page instead of retyping it.
• Process invoices: pull amounts, dates, and reference numbers out of faxed or scanned invoices without manual entry.
• Make screenshots quotable: a screenshot saved into a PDF becomes copyable text in seconds.
• Revive legacy archives: convert decades-old scanned reports into text you can actually work with.

Tips for Better OCR Accuracy

OCR quality depends heavily on the scan and the settings you choose. A few habits can reduce the cleanup work:

• Correct orientation. In our challenge, a sideways page measured 8.08% character accuracy without correction and 97.60% after selecting Rotate 90° clockwise.
• Preserve enough character detail. Our large 14-point text remained readable in a 100 DPI source, but that does not generalize to fine print. Higher source resolution gives small characters more pixels to work with.
• Aim for good contrast. Dark text on a clean white background works best. Faded ink, colored paper, and shadows from phone photos all hurt accuracy.
• Pick the right language. Running a Spanish document through the English model will mangle accented characters.
• Proofread the output. Even good OCR makes occasional mistakes, especially with numbers, names, and unusual fonts.