PDF OCR — Extract Text from Scanned PDFs

A scanned page is a grid of pixels — to your PDF reader, a photograph. OCR runs a recognition pipeline over it: the page is straightened and cleaned (deskewing and binarization), text regions are detected and segmented into lines and characters, each character shape is matched against trained models, and a language dictionary resolves ambiguous shapes — deciding that "c0ntract" was almost certainly "contract". The Tesseract engine used here is the same open-source OCR that powers document pipelines across the industry.

Resolution and contrast dominate. A laser-printed page scanned at 300 DPI recognizes at 95%+ accuracy; the same page at 150 DPI or photographed at an angle drops noticeably. The practical rules: scan at 300 DPI in grayscale, keep the page flat (book gutters and receipt creases cast shadows that read as marks), and set the correct document language before running — dictionary matching is language-specific.

After OCR, spot-check the fields where errors are expensive: names, reference numbers, and currency amounts. Recognition errors cluster in visually similar characters, so a "5" that became an "S" in an invoice total is the failure mode to catch.

This tool outputs the recognized text for copying or download as .txt — the fastest route when you need the content, not the layout: quoting a scanned contract, digitizing receipt data, or preparing text for translation. To rebuild an editable document, paste into Word or take the text through the PDF to Word workflow; to fix a few words directly on the scanned page, use the PDF Text Editor's overlay mode on the original file.