Stephan Olbrich, Andreas Beckert, Cécile Michel, Christian Schroer, Samaneh Ehteram, Andreas Schropp, Philipp Paetzold
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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. 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引用次数: 0
摘要
楔形文字是已知最早的书写系统,最早是在公元前 4 世纪后半期为美索不达米亚南部的苏美尔语而开发的。楔形文字的符号是通过在新鲜粘土片上刻画笔迹而获得的。出于某些目的,例如通过印章印记进行鉴定,一些楔形文字石碑被装在粘土封套中,如果不破坏封套就无法打开。我们的跨学科项目旨在对泥板进行无损伤研究。我们开发了一种便携式 X 射线显微 CT 扫描仪,可在采集地点的高分辨率、规则三维网格上获取此类文物的密度数据。通过特征保留去噪、使用流形双行进立方体算法提取高精度表面以及通过增强曲率渲染和环境遮挡提取局部特征,对得到的体积数据进行处理。在对楔形文字铭文进行非侵入式研究时,通过基于曲率的分割,将碑文与其封套几乎分离开来。对计算和数据密集型算法进行了优化,以便在收集地点资源有限的情况下进行近乎实时的离线使用。为了使复杂度降低和基于八度压缩的表面表示可视化,我们开发并实现了一个交互式应用程序。为便于分析此类泥板,我们实施了基于形状的特征提取算法,以提高楔形文字的识别能力。我们的工作流程支持创新的三维显示和交互技术,如自立体显示和手势控制。
Efficient Analysis and Visualization of High-Resolution Computed Tomography Data for the Exploration of Enclosed Cuneiform Tablets
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.