Optical character recognition transforms image-based PDF pages into searchable, selectable text. Our OCR engine processes each page in three stages: image preprocessing, character recognition, and layout reconstruction.
Preprocessing includes automatic deskewing to correct pages scanned at slight angles, binarization to improve contrast between text and background, and noise removal to eliminate scanning artifacts. These steps improve recognition accuracy by 15-30% on typical scanned documents.
The recognition engine supports 107 languages including Latin, Cyrillic, Greek, Arabic, Hebrew, and CJK character sets. Mixed-language documents are handled automatically through script detection at the word level.
Layout reconstruction preserves the visual structure of the original document. Columns, headers, footers, captions, and marginal notes are identified and tagged appropriately. The resulting PDF contains an invisible text layer overlaid on the original scanned images.
Batch processing supports up to 500 pages per session. A progress indicator shows estimated completion time based on page complexity and selected language models.