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PDF OCR – Extract Text

Extract selectable text from a scanned PDF or image using optical character recognition.

A scanned document — a photographed receipt, an old printed contract, a screenshot of text — is just a picture as far as your computer is concerned, with no selectable, searchable, or copyable text underneath. Optical Character Recognition (OCR) analyzes the image and identifies the actual characters, converting a picture of text into real, usable text.

This tool runs OCR entirely in your browser using Tesseract, a mature, widely-used open-source OCR engine (originally developed at HP, now maintained by Google) compiled to run via WebAssembly — the same underlying recognition technology used in many commercial OCR products, running locally rather than uploading your document to a cloud OCR API. It works on both PDFs (extracting text page by page, with results concatenated together) and standalone images (PNG/JPG).

OCR accuracy depends heavily on the source image's quality — a clean, high-contrast scan of typed text will recognize nearly perfectly, while handwriting, low resolution, skewed pages, or poor contrast will produce more errors. Selecting the correct document language also matters, since the recognition model is language-specific.

How to use PDF OCR – Extract Text

  1. 1

    Upload your PDF or image

    Drop a scanned PDF or an image file into the upload area.

  2. 2

    Choose the document language

    Select the language the text is written in for accurate recognition.

  3. 3

    Click Extract Text

    Watch the live progress as OCR processes each page, then review the extracted text.

  4. 4

    Copy or download the result

    Grab the extracted text as plain text, ready to paste or save.

Features

  • Real OCR using the mature open-source Tesseract engine
  • Processes both PDFs (page by page) and standalone images
  • Supports 5 languages with dedicated recognition models
  • Runs entirely in your browser — no upload, no cloud OCR API

Frequently asked questions

Common mistakes to avoid

  • Selecting the wrong document language, which significantly reduces recognition accuracy.
  • Expecting high accuracy on low-resolution, skewed, or handwritten source material.
  • Not reviewing extracted text for errors before relying on it for something important — always proofread OCR output.
Written by Converter Portal Editorial TeamPublished June 25, 2026Last updated June 25, 2026

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