⚙️ Advanced PDF

🔍 OCR PDF

Extract text from scanned PDF pages with optical character recognition.

OCR PDF reads selected scanned pages using one of six languages and adds an invisible text layer for supported characters. If the PDF font cannot represent recognized characters, a separate UTF-8 text download preserves the full recognized text. Review OCR results for errors.

🔍 OCR PDF Files stay in your browser
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Drop PDF file here
or click to browse · Up to 1 file · 80 MB max

    Choose a file to begin.

    Tool guidance maintained by Leslie 路 Updated November 6, 2026. Report an incorrect result.

    How to use OCR PDF

    1. Upload a scanned PDF.
    2. Choose the OCR language and pages.
    3. Click OCR PDF and wait for the browser to finish.
    4. Download the PDF and any accompanying text file, then check the recognized text.

    Features

    • Runs Tesseract OCR in the browser
    • Six language packs
    • Searchable PDF output
    • Document recognition stays in your browser

    OCR runs in your browser. Worker, engine, and language files are loaded from this site. Recognition accuracy and word-level selection alignment are not guaranteed; some characters may be available only in a separate text download.

    Worked example: Make a 45-line English scan searchable

    Tested October 17, 2026 with synthetic, non-sensitive files on this website. The files below are the inputs and actual browser-downloaded outputs from that test.

    Find a reference number in a scan without reading every line. Our sample is a single image-only page with 45 lines and reference numbers 1001–1045.

    Try the example

    1. Download the input scan below and choose it in the tool.
    2. Select English and leave Pages set to all, then run OCR.
    3. Download the result and search for 1001, 1040, and 1045 in a PDF reader.

    What we observed

    • The downloaded PDF contained one page and extractable text with all 45 reference numbers, including the final five lines.
    • The scan image remained visible. Some punctuation differed from the input, so a searchable result is not necessarily an exact transcription.

    When this is useful

    Clear printed scans in a supported language when you need to find words or copy a draft of the text.

    Limits of this example

    This example tests English only, not every language, handwriting, or complex columns. Selection highlights need not align with the words in the scan. Unsupported font characters may be available only in an accompanying TXT file.

    Check your own output

    Compare names, amounts, and reference numbers with the image. Check the last lines as well as the first page. If text is missing, inspect any accompanying TXT file and try a clearer scan or the correct language.

    Select the pages and language that need recognition

    For a ten-page scan where only pages 4-6 need searchable text, selecting 4-6 creates a three-page output containing those pages. It does not return all ten pages with only a subset updated. Choose the language matching the scan from the six offered packs; recognition is not translation.

    Pages are rendered as images with an invisible recognized-text layer. Search for a distinctive phrase, then check names, amounts, and punctuation against the scan. Highlight positions need not align with individual words. If the PDF font cannot represent some recognized characters, download the accompanying UTF-8 TXT for the full recognized text. Existing forms and interactive PDF elements are not retained by this image-based rebuild.

    Frequently asked questions

    Yes. The tool renders each page and recognizes text with Tesseract OCR.

    English, Spanish, French, German, Italian, and Portuguese language data are available.

    Supported characters are included in an invisible PDF text layer. If recognized characters are unsupported by the PDF font, a separate UTF-8 text download includes the full recognized text.

    Accuracy depends on scan quality, language, layout, and text clarity. No accuracy percentage is guaranteed. Review recognized text against the original, especially names and numbers.