An image-based approach for High-Density Data Encoding on Paper

Barcodes are one of the most prevalent techniques for representing digital information on physical printed media. Standardized symbologies, such as QR Code and Data Matrix, are built to be employed in industrial and consumer settings and their design prioritizes robustness, ease of use, and compatibility. While effective and essential in their application fields, these standards do not aim to maximize the density and capacity of barcode symbols leaving open the question of how much information can be realistically stored on paper. This thesis project investigates the design and implementation of an experimental system for high-density, high-capacity paper data storage. The development of the system focuses on overcoming the technical and physical limitations of printing and scanning processes, exploring the trade-offs between capacity, robustness and decodability. Experimental results are compared against conceptually similar applications and show that the system can store up to ∼ 300 kilobytes of data per A4 page while remaining decodable under realistic printing and scanning conditions.