You open a PDF and try to select a sentence to copy. Nothing highlights. Dragging your cursor across the page selects the whole thing as a single image. The document came from a scanner, which means every page is a photograph of text rather than actual text data. Ctrl+F finds nothing. Ctrl+C gives you nothing useful. The content is effectively locked inside the image, and the only way to get it out is OCR.
This problem shows up constantly with scanned contracts, government documents, old academic papers, bank statements, archived reports, and any PDF created by pointing a scanner or phone camera at a physical page. This tool handles both cases in one interface: digital PDFs where text can be extracted instantly from the text layer, and scanned PDFs where Tesseract.js runs optical character recognition directly in your browser to recognize and extract the characters from the page images. Seven languages are supported. Nothing is uploaded to any server at any point.
How It Works
- Upload your PDF by dragging it onto the upload area or clicking to browse. The tool reads the file and parses its structure to determine whether a text layer is present. A confirmation appears once the file is loaded and ready for extraction.
- Choose an extraction method from three options. Auto mode tries the text layer first and falls back to OCR if no selectable text is found, which is the right choice when you are not sure whether a PDF is digital or scanned. Text Layer mode extracts text directly from the PDF structure instantly, with no OCR processing. OCR Scan mode forces Tesseract.js to analyze the page images regardless of whether a text layer exists, which is the correct choice for confirmed scanned documents. For OCR Scan mode, also select the document language from the available options: English, Urdu, Hindi, Arabic, Spanish, French, or German. Matching the language to the document improves recognition accuracy significantly.
- Extract and save the text by clicking Extract Text. The tool processes the document through reading, analyzing, extracting, and formatting stages, then displays the result with a word count. Copy the extracted text directly to clipboard, or download it as a .txt file for use in any text editor, word processor, or data workflow.
Compatibility & Support
Supported Input → Output Formats
- Input: Standard PDF (digital with text layer) and scanned/image-based PDFs
- Output: Plain text via clipboard copy, or .txt file download
- Extraction modes: Auto (smart fallback), Text Layer (instant), OCR Scan (image recognition)
- OCR languages: English, Urdu, Hindi, Arabic, Spanish, French, German
Unsupported Formats
The tool processes PDF files only. Standalone image files (JPG, PNG, TIFF) cannot be uploaded directly; convert them to PDF first. Very low-resolution scans below approximately 150 DPI will produce lower OCR accuracy because Tesseract.js requires sufficient pixel density to reliably distinguish characters. Password-protected PDFs that restrict content access cannot be processed until the restriction is removed.
File Size Limits
Digital text extraction via the Text Layer method runs instantly regardless of page count since it reads the PDF structure directly. OCR Scan mode downloads Tesseract.js language weights to your browser cache on first use, then processes pages locally. Large scanned documents with many pages will take proportionally longer to process since each page image must be analyzed individually, but no external server imposes a size restriction.
Who Should Use This Tool?
- Students: A student who has downloaded a scanned journal article and needs to quote a specific passage can run OCR extraction and copy the recognized text rather than retyping every word from a PDF they cannot interact with normally.
- Freelancers & Designers: A translator working with a scanned legal document in Arabic or Spanish can select the matching OCR language to improve character recognition accuracy before extracting the full text into their working translation file.
- Office Professionals: An accounts clerk receiving scanned invoices as PDFs can extract the supplier names, amounts, and reference numbers using OCR, then paste the extracted text into a spreadsheet or accounting system without manual retyping.
- Developers: A developer building a document intake pipeline can use this tool to test OCR accuracy on sample scanned PDFs in multiple languages before committing to a server-side Tesseract integration for production processing.
Key Features
Here's what separates this tool from generic alternatives:
No Server Upload
Digital text extraction runs locally in the browser. For OCR, Tesseract.js downloads language weights to your browser cache and processes pages on your device. Scanned medical records, contracts, and personal documents never leave your machine.
Auto Detection Mode
Auto mode checks for a text layer first and only runs OCR if no selectable text is found. This means digital PDFs extract instantly while scanned PDFs trigger the OCR pass automatically, without you needing to know which type you have.
Seven OCR Languages
English, Urdu, Hindi, Arabic, Spanish, French, and German are all supported. Selecting the correct language significantly improves recognition accuracy for non-Latin scripts and accented characters that generic OCR tools often misread.
Instant Text Layer Extraction
For standard digital PDFs, Text Layer mode extracts all text from the PDF structure in seconds without OCR processing. This is the fastest path for any PDF where the content is already selectable.
TXT File Download
Download the extracted text as a .txt file alongside the clipboard copy option. Plain text files open in any editor or word processor and feed cleanly into translation tools, data pipelines, and content management systems.
Word Count on Completion
The tool shows the total word count of extracted text once processing is complete. Useful for confirming that a full document was processed and for checking OCR coverage before using the output in a word-count sensitive workflow.
Why This Tool Beats the Alternatives
- No account, email, or signup required at any point.
- No watermarks or hidden usage limits on the free tier.
- No server upload; Tesseract.js runs OCR locally, which is critical for scanned personal documents and confidential files.
- Seven OCR languages including Arabic, Hindi, and Urdu, which most basic free OCR tools do not support.
- Auto mode detects text layer vs. scanned content automatically, removing the need to diagnose the PDF type before extracting.
- Both clipboard copy and .txt download are available without any paid tier requirement.
Pro Tips
- If Auto mode produces incomplete or garbled text from a document that looks digital, switch to OCR Scan mode. Some PDFs have technically present text layers that are corrupted or encoded in a way that produces gibberish on extraction. Forcing OCR treats the page as an image and reads it visually, which often produces cleaner output in these cases.
- For best OCR accuracy on scanned documents, always select the language that matches the document before extracting. For a Hindi-language scanned contract, selecting English and running OCR will misread many characters. Selecting Hindi directs Tesseract.js to use the correct character set and language model, significantly improving the output.
- OCR language weights download to your browser cache the first time you use each language. If you plan to process multiple scanned PDFs in the same session, keep the browser tab open between files rather than refreshing. The language weights stay cached, making each subsequent extraction faster than the first.
Upload your PDF, choose the extraction method that fits your document type, and copy or download the text output in seconds. If the PDF also contains links you need to collect alongside the text, the Extract URLs from PDF tool handles link extraction in the same browser-based workflow.