OCR PDF Free – Extract Text from Scanned PDF

🛡️Files stay on your device

🔍Tesseract.js OCR engine

📋No sign-up

📄100+ languages

ℹ️ First use note: Tesseract.js downloads a language model (~10 MB) on first run. This may take 20–40 seconds depending on your connection. After that, OCR runs instantly offline.

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Drag & Drop Your Scanned PDF Here

Upload a scanned or image-based PDF to extract its text

📂 Select PDF File

⚙️ OCR Options

Language

Resolution

Initialising OCR engine…

✅

Text Extracted Successfully!

OCR result will appear here…

HOW IT WORKS

PDF OCR in 3 Steps

Upload Scanned PDF

Select any image-based or scanned PDF document.

OCR Processes Each Page

PDF.js renders each page to a canvas at high resolution. Tesseract.js reads the text from each image sequentially.

Copy or Save Text

Copy all extracted text to your clipboard or save it as a .txt file.

How Browser-Based PDF OCR Works

OCR (Optical Character Recognition) extracts text from image-based content. PDFScanner uses a two-step pipeline: first, PDF.js renders each PDF page onto an HTML5 Canvas at 3× scale to ensure high-resolution input for the OCR engine. Then Tesseract.js (a WebAssembly port of Google's Tesseract OCR engine) processes each canvas image sequentially and extracts the text with bounding-box sorting.

When to Use OCR vs Standard Text Extraction

If your PDF was created digitally (from Word, Excel, etc.), its text is already embedded and can be selected and copied directly in any PDF viewer — OCR is not needed. OCR is for PDFs that are essentially images: documents scanned from paper, photographed pages, or PDFs exported from image-only sources.

OCR Accuracy Tips

Use the "High" resolution setting for best accuracy on dense text
Clean, high-contrast scans produce significantly better results than blurry or low-contrast images
Select the correct language for your document's content
Hand-written text is not reliably recognised by Tesseract — OCR works best on printed text

FAQ

OCR PDF — FAQ

How accurate is the OCR?▼

Tesseract.js achieves 95%+ accuracy on clean, high-resolution scans of printed text in supported languages. Accuracy decreases with blurry images, unusual fonts, complex layouts, or handwriting.

Why is OCR slow on multi-page PDFs?▼

OCR is computationally intensive. Each page is rendered to a high-resolution canvas and then processed by the Tesseract engine running in WebAssembly. A 10-page document may take 30–90 seconds depending on your device's CPU speed.

Can I OCR handwritten text?▼

Tesseract is optimised for printed text. Handwriting OCR requires specialised neural models and will generally produce poor results with this tool.

Why is the first run slow?▼

Tesseract.js downloads a trained language model file (~10 MB) on its first use. This is cached by your browser, so subsequent runs are faster. You can also use the tool offline once the model is downloaded.