An Intelligent Machine-Driven Perspective to Archaeological Pottery Reassembly

Abstract

Information and communication technologies (ICT) have been at the centre of most innovations. With applications in science, technology, engineering, and mathematics fields, it has become prevalent in business, art, and humanities disciplines, among others, as well. Among the potential applications of ICT in social sciences and digital humanities, documentation and reconstruction of archaeological artefacts have garnered interest and resulted in several studies. This is because of the potential inherent in these artefacts for archaeological and historical studies. However, regarding pottery reassembly, challenges are experienced in implementing an optimal solution entailing high standards. Although existing studies attempted to solve these challenges, a high standard solution is still elusive. This article presents an approach to a machine-driven solution that intends to use computer vision and machine learning, whose potential is yet to be felt in pottery reassembly. This investigation, still at an early stage, has profound implications for future studies in pottery studies in general.