An alternative clustering approach for reconstructing cross cut shredded text documents

摘要

In this paper, we propose a clustering approach for solving the problem of reconstructing cross-cut shredded documents. This problem is important in the field of forensic science. Unlike other clustering approaches which are applied as a preprocessing step before the actual reconstruction algorithms, our clustering approach is part of the reconstruction process itself. We define a new cost function which mainly relies on black pixels to measure the cost of pairing two shreds together. The reconstruction algorithm creates multiple clusters which grow by adding additional shreds based on the cost function. Adding a shred may result in merging two or more clusters to produce a larger cluster. We, also, propose a way to involve the user in the reconstruction process. We compare our approach with a recent proposal and conclude that our approach gives better solutions in less time.