Image-based PDFs contain scanned images of text pages, meaning they function like photographs with no computer-readable text. To make these searchable, Optical Character Recognition (OCR) technology is applied. OCR software analyzes the image, identifies shapes representing letters, numbers, and symbols, and translates them into actual digital text. This text is then embedded as an invisible layer behind the original image within the PDF file, enabling search functions to find words within the document content.

For example, libraries and archives often use OCR on historical scanned documents to allow researchers to search through vast collections. In business, a law firm might OCR signed contract scans received via email to quickly locate specific clauses or terms later. Common tools for OCR include Adobe Acrobat Pro (feature often named 'Scan & OCR'), dedicated OCR software like ABBYY FineReader, or free open-source solutions like Tesseract (often integrated into other tools). Online PDF converters also frequently offer OCR services.

This process dramatically improves accessibility and efficiency when handling scanned documents. However, OCR accuracy depends heavily on original image quality and clarity; smudges, complex layouts, or unusual fonts may lead to errors. Manual verification is sometimes needed. Future advancements involve AI enhancing accuracy, especially for challenging documents. Ethically, OCR emphasizes the importance of data handling for sensitive information, as data becomes extractable, making proper document redaction crucial.