![]() Our role was to focus on pairwise fitting of fracture surfaces belonging to fragments, nominated by other selection modules in the system, by aligning the fragments to an accuracy compatible with the digitization noise expected within the scanning process (or report failure to the selection module). Our method is part of a larger system for reunification of broken archaeological artefacts in the GRAVITATE project (Phillips et al., 2016). These demands, paired with a sensible time behaviour, make pairwise alignment a daunting computational task (as other studies such as (Toler-Franklin et al., 2010 McBride and Kimia, 2003 Palmas et al., 2013) confirm). Moreover, their digital mesh representation may contain digitization noise and point cloud registration errors from the 3D scanning process. Typically, archaeological artefacts are not only broken, but their fractures may be incomplete (e.g., if the artefact was broken again and the other piece is missing), abraded, or even deformed. Even a single accurate alignment may considerably affect the cultural interpretation of artefacts (Sommella Mura, 2011), so accuracy is required. This may involve the virtual fitting or reassembly of broken objects, dispersed over different collections, or simply too heavy to be manipulated physically. Virtual archaeology, the study of artefacts by means of their digital representations, should enable an archaeologist to perform common workflow tasks remotely. We show that our morphological method outperforms a recent linear pairwise alignment method and briefly discuss our limitations and the effects of variations in digitization and abrasion on our proposed alignment technique. Careful quantitative evaluation on real terracotta fragments confirms the accuracy of our method under the expected archaeological noise. We propose new criteria for evaluating the resulting pairwise alignment quality, taking into consideration both penetration and gap regions. This compact morphological representation provides the information required for accurately aligning the fracture surfaces through applying a RANSAC-based algorithm incorporating weighted Procrustes to the morphological features, followed by ICP on morphologically selected ‘flank’ regions. Such features and their descriptors are computed by analysing the discrete distance transform and its causal scale-space information. ![]() In our approach, the fracture surface is tightly bounded by a concise set of characteristic multi-local morphological features. ![]() We propose to use the non-linear complementarity-preserving properties of Mathematical Morphology to guide the pairwise fitting in a manner inherently insensitive to these aspects. ![]() The challenge is to achieve an accurate fit, even though the data is inherently lacking material through abrasion, missing geometry of the counterparts, and may have been acquired by different scanning practices. We design a computational method to align pairs of counter-fitting fracture surfaces of digitized archaeological artefacts. ![]()
0 Comments
Leave a Reply. |