In-Browser PDF OCR

Recognise and extract editable text from scanned PDF pages and documents locally. No file uploads, no cloud APIs, and complete data confidentiality.

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🔒 Zero-Upload Confidential OCR

Standard online OCR tools transmit your sensitive PDF files, scanned contracts, invoices, and bank statements to remote servers. BWTools executes the entire Optical Character Recognition process inside your browser sandbox via WebAssembly. Your files never leave your device.

⚡ Multi-Page Neural Inference

Extract clean, structured text from single pages or multi-page documents seamlessly. Each page is rasterised at optimal DPI and analysed using deep-learning character recognition networks optimised for Latin scripts, punctuation, and tabular layouts.

How to Extract Text from PDF Documents

  1. Choose the primary language of your document from the drop-down menu (defaulting to English).
  2. Drag and drop your PDF file onto the dropzone or press Browse to select it from your local storage.
  3. Wait briefly while the client-side Web Worker rasterises each page canvas and recognises characters sequentially.
  4. Review the extracted text, inspect confidence indicators, copy text with Ctrl+C / Cmd+C, or download as a .TXT or .JSON file.

Client-Side Architecture & Engine Pipeline

The optical character recognition pipeline operates in two synchronised stages:

  • Vector Rasterisation (pdf.js): PDF viewports are parsed into raw pixel buffers via HTML5 Canvas at an upscaled resolution factor of 2.0x to maximise character edge contrast.
  • Neural Inference (Tesseract.js WASM): The rasterised canvas pixel data is transferred into a multi-threaded Web Worker running Tesseract's compiled WebAssembly neural engine with LSTM models.

Engine Specifications & Performance Targets

Parameter Specification Recommended Usage
Supported Input Standard & Scanned PDF (.pdf) Multi-page documents up to 50 pages
Output Formats Plain Text (.txt), Structured Data (.json) Document indexing, data entry, copy-pasting
Language Models English, French, German, Spanish, Italian, Dutch, Portuguese Latin script scanned materials
Processing Rate ~1.2 to 2.8 seconds per page Depends on client CPU and document complexity

Frequently Asked Questions

Are my confidential documents uploaded to any server? ▼

No. The entire process runs 100% in your local browser runtime. No PDF pages, rendered canvas frames, or extracted strings ever leave your computer.

How can I improve character recognition accuracy? ▼

Ensure the source PDF has good contrast and lighting. Our engine automatically applies a 2.0x resolution upscale during rasterisation to maximise recognition fidelity.

Can I process password-protected PDFs? ▼

Encrypted files must first be unlocked before OCR processing. You can remove restrictions using our client-side PDF Protect utility prior to running character recognition.