Stephan Olbrich, Andreas Beckert, Cécile Michel, Christian Schroer, Samaneh Ehteram, Andreas Schropp, Philipp Paetzold
{"title":"Efficient Analysis and Visualization of High-Resolution Computed Tomography Data for the Exploration of Enclosed Cuneiform Tablets","authors":"Stephan Olbrich, Andreas Beckert, Cécile Michel, Christian Schroer, Samaneh Ehteram, Andreas Schropp, Philipp Paetzold","doi":"arxiv-2409.04236","DOIUrl":null,"url":null,"abstract":"Cuneiform is the earliest known system of writing, first developed for the\nSumerian language of southern Mesopotamia in the second half of the 4th\nmillennium BC. Cuneiform signs are obtained by impressing a stylus on fresh\nclay tablets. For certain purposes, e.g. authentication by seal imprint, some\ncuneiform tablets were enclosed in clay envelopes, which cannot be opened\nwithout destroying them. The aim of our interdisciplinary project is the\nnon-invasive study of clay tablets. A portable X-ray micro-CT scanner is\ndeveloped to acquire density data of such artifacts on a high-resolution,\nregular 3D grid at collection sites. The resulting volume data is processed\nthrough feature-preserving denoising, extraction of high-accuracy surfaces\nusing a manifold dual marching cubes algorithm and extraction of local features\nby enhanced curvature rendering and ambient occlusion. For the non-invasive\nstudy of cuneiform inscriptions, the tablet is virtually separated from its\nenvelope by curvature-based segmentation. The computational- and data-intensive\nalgorithms are optimized or near-real-time offline usage with limited resources\nat collection sites. To visualize the complexity-reduced and octree-based\ncompressed representation of surfaces, we develop and implement an interactive\napplication. To facilitate the analysis of such clay tablets, we implement\nshape-based feature extraction algorithms to enhance cuneiform recognition. Our\nworkflow supports innovative 3D display and interaction techniques such as\nautostereoscopic displays and gesture control.","PeriodicalId":501174,"journal":{"name":"arXiv - CS - Graphics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.04236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Cuneiform is the earliest known system of writing, first developed for the
Sumerian language of southern Mesopotamia in the second half of the 4th
millennium BC. Cuneiform signs are obtained by impressing a stylus on fresh
clay tablets. For certain purposes, e.g. authentication by seal imprint, some
cuneiform tablets were enclosed in clay envelopes, which cannot be opened
without destroying them. The aim of our interdisciplinary project is the
non-invasive study of clay tablets. A portable X-ray micro-CT scanner is
developed to acquire density data of such artifacts on a high-resolution,
regular 3D grid at collection sites. The resulting volume data is processed
through feature-preserving denoising, extraction of high-accuracy surfaces
using a manifold dual marching cubes algorithm and extraction of local features
by enhanced curvature rendering and ambient occlusion. For the non-invasive
study of cuneiform inscriptions, the tablet is virtually separated from its
envelope by curvature-based segmentation. The computational- and data-intensive
algorithms are optimized or near-real-time offline usage with limited resources
at collection sites. To visualize the complexity-reduced and octree-based
compressed representation of surfaces, we develop and implement an interactive
application. To facilitate the analysis of such clay tablets, we implement
shape-based feature extraction algorithms to enhance cuneiform recognition. Our
workflow supports innovative 3D display and interaction techniques such as
autostereoscopic displays and gesture control.