Unshredding of Shredded Documents: Computational Framework and Implementation
This addresses the challenge of recovering confidential information from shredded documents, which is important for forensic analysis and security purposes, but it appears incremental as it builds on existing computational methods for document reconstruction.
The paper tackles the problem of reconstructing shredded documents by presenting an optimal O((n×m)^2) algorithm that works for hand-written, machine typed-set, and image documents, achieving reconstruction of shredded pages into their original form.
A shredded document $D$ is a document whose pages have been cut into strips for the purpose of destroying private, confidential, or sensitive information $I$ contained in $D$. Shredding has become a standard means of government organizations, businesses, and private individuals to destroy archival records that have been officially classified for disposal. It can also be used to destroy documentary evidence of wrongdoings by entities who are trying to hide $I$. In this paper, we present an optimal $O((n\times m)^2)$ algorithm $A$ that reconstructs an $n$-page $D$, where each page $p$ is shredded into $m$ strips. We also present the efficacy of $A$ in reconstructing three document types: hand-written, machine typed-set, and images.