Discrete Grey Wolf Optimization for Shredded Document Reconstruction

Abstract

Shredded document reconstruction problem has gained more attention in the last few years. The reconstruction process is commonly involved in forensics, investigation sciences, and reconstruction of destroyed archaeological papyrus and manuscripts. Exhaustive search is common for handling such problem for small dimensions but with higher dimension, the problem becomes worse. Recently, a bio-inspired grey wolf optimizer (GWO) is a great algorithm for solving continuous problem but the nature of Shredded document reconstruction is a discrete problem, so a discrete version of GWO has been proposed and applied to it, This paper also proposed a general simple fitness function that can handle both text and image-based documents.