When you scan an old invoice, book page, or paper contract with an office scanner or phone camera, the resulting PDF is simply a container of flat pixel images. You cannot search for keywords, highlight sentences, or copy-paste text. Optical Character Recognition (OCR) solves this by analyzing visual glyph shapes and generating a searchable text layer.
#1How Optical Character Recognition Works Under the Hood
The OCR pipeline begins with pre-processing: converting color images to high-contrast binary monochrome, deskewing tilted angles, and removing scanning artifacts. Next, machine learning neural nets segment lines and words, matching pixel contours to known font geometries.
Historically, performing OCR required heavy cloud APIs that cost money per page and uploaded your confidential receipts to corporate servers. MistPDF runs Tesseract WebAssembly directly on your computer's local hardware.
#2Creating True Searchable PDFs vs. Plain Text Extraction
MistPDF provides two output options for recognized documents: Plain Text (.txt) for instant copy-pasting into spreadsheets, or Searchable PDF.
A Searchable PDF retains the original visual scan while embedding an invisible, perfectly aligned vector text layer underneath each image. This allows you to press Ctrl+F (Cmd+F) in any PDF viewer and search through the document as if it were natively typed.
Conclusion
Unlock your scanned archives and paper documents. Transform flat images into searchable, actionable knowledge with MistPDF's local OCR engine.
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Does client-side OCR require an internet connection?
Once the WebAssembly OCR engine is cached in your browser on initial load, OCR works completely offline without sending any data over the web.
What languages are supported by MistPDF OCR?
The built-in engine supports English, Spanish, French, German, Italian, Portuguese, and standard Latin script alphabets with high character recognition precision.