An automatic positioning algorithm for archaeological fragments

One of the main challenges on digital preservation of cultural heritage is to reassemble broken fragments. However, large amounts of fragments are mixed randomly when discovered, which brings terrific difficulties for their reassembly. This paper introduces an automatic approach for positioning large mixed archaeological fragments which come from a particular kind of artifact. The main idea is to position fragments based on partial matching between fragments and a complete artifact model using the multi-scale, informative and robust Heat Kernel Signature. The positioning pipeline contains four steps: feature points extraction for fragments and the complete artifact model based on Heat Kernel Signature; initial matching between feature points by comparing their Heat Kernel Signature curves; wrong matches removing using a basis points driven refinement procedure and rigid transformation generating by selecting three pairs of points among the correct matching results using farthest points sampling. After these steps, archaeological fragments can be positioned to different positions compared with the template model, which provides not only the classification information, but also the accurate relative position. The main contributions of this paper are using a novel feature extraction algorithm based on Heat Kernel Signature to assist partial matching, and a basis points driven refinement procedure to remove wrong matches. The proposed algorithm has been tested on the Terracotta Warriors fragments, and the results prove the effectiveness of the proposed positioning algorithm.