Reconstructing Cross-Cut Shredded Text Documents: A Genetic Algorithm with Splicing-Driven Reproduction

Abstract

In this work we focus on reconstruction of cross-cut shredded text documents (RCCSTD), which is of high interest in the fields of forensics and archeology. A novel genetic algorithm, with splicing-driven crossover, four mutation operators, and a row-oriented elitism strategy, is proposed to improve the capability of solving RCCSTD in complex space. We also design a novel and comprehensive objective function based on both edge and empty vector-based splicing error to guarantee that the correct reconstruction always has the lowest cost value. Experiments are conducted on six RCCSTD scenarios, with experimental results showing that the proposed algorithm significantly outperforms the previous best-known algorithms for this problem.