journal article·2022-03Open access

A high-resolution photogrammetric workflow based on focus stacking for the 3D modeling of small Aegean inscriptions

Roberta Ravanelli, Lorenzo Lastilla, Silvia Ferrara

Abstract

Any attempt of decipherment and language identification of the scripts from the Aegean dating to the second millennium BCE (namely Cretan Hieroglyphic, Linear A, and Cypro-Minoan) has relied, until today, on traditional catalogues of inscriptions, consisting of incomplete or subjective 2D representations, such as photographs and hand-drawn copies, which are not suitable for documenting such three-dimensional writing systems. In contrast, 3D models of the inscribed media allow for an accurate and objective “autopsy” of the entire surface of the inscriptions. In this context, this work presents an efficient, accurate, high-resolution, and high-quality texture photogrammetric workflow based on focus-stacked macro images, designed for the 3D modeling of small Aegean inscriptions, to properly reconstruct their geometry and to enhance the identification of their signs, making their transcription as unbiased as possible. The pipeline we propose also benefits from a pre-processing stage to remove any coloration difference from the images, and a reliable and simple 3D scaling procedure. We tested this workflow on six inscribed artifacts (two in Cretan Hieroglyphic, three in Linear A, one of uncertain affiliation), whose average size ranges approximately from 1 to 3 cm. Our results show that this workflow achieved an accuracy of a few hundredths of mm, comparable to the technical specifications of standard commercial 3D scanners. Moreover, the high 3D density we obtained (corresponding to the edge average length of the 3D model mesh), up to ≈ 30 μm, allowed us to reconstruct even the smallest details of the inscriptions, both in the mesh and in the texture layer of the 3D models.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: 3D Surveying and Cultural Heritage · Optical measurement and interference techniques · Advanced Vision and Imaging

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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