Preserving Heritage with AI-Driven PDF Restoration

Across libraries, temples, research institutions, trusts, and private collections worldwide, millions of valuable books, manuscripts, journals, and archival documents exist only in degraded PDF or scanned formats. These documents often suffer from yellowed pages, faded text, stains, stamps, handwritten markings, shadows, skewed scans, low resolution, blank pages, and inconsistent formatting, making them difficult to read, preserve, search, or distribute digitally. Despite the growing importance of digital preservation and AI-driven knowledge accessibility, there is currently no scalable and user-friendly platform specifically designed to transform poor-quality archival PDFs into clean, digitally optimized documents while preserving their authenticity. This project aims to build an advanced AI-powered web platform that automatically converts old, damaged, stamped, noisy, or low-quality PDF documents into clean, publication-ready digital PDFs. The platform will enhance readability, remove unwanted artifacts, eliminate blank pages, correct orientation and alignment issues, improve contrast and sharpness, and optionally remove institutional stamps through AI-assisted or manual review workflows. Beyond PDF cleanup, the vision is to create a digital restoration ecosystem that empowers libraries, scholars, publishers, spiritual organizations, and archival institutions to modernize valuable knowledge into accessible, searchable, and professionally presentable digital assets. The proposed system will combine image processing, OCR enhancement, AI-based document restoration, and intuitive web workflows to make large-scale digitization practical, affordable, and accurate. Ultimately, this initiative seeks to bridge the gap between historical knowledge preservation and modern digital accessibility, ensuring that invaluable cultural and intellectual heritage can be preserved and utilized for future generations.