High-Fidelity Scanned Document Digitization and Layout Reconstruction
Pain Points (Public)
Organizations accumulate backlogs of image-based scans such as legacy contracts or archival records that cannot be searched or modified. Standard OCR tools frequently scramble table borders, drop list nesting, and produce character errors, while pure manual re-typing into Microsoft Word is prohibitively slow and error-prone.
Suggested Approach (Public)
An end-to-end document processing pipeline that pairs visual layout analysis (detecting tables, headings, and list structures) with OCR correction and automated .docx generation, supplemented by a focused verification UI for rapid typo proofing.
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Public Demand Evidence · 2 task(s)
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