arXiv:2410.07385cs.CVeess.IV2024-10被引 2

用10次扫描处理1112个动物骨片,实现小物体高分辨率批量成像。

En masse scanning and automated surfacing of small objects using Micro-CT

  • 批量扫描+自动化处理,内存受限设备也能运行。
  • 1112个骨片仅需10次微CT扫描,生成独立PLY文件。
  • 适用于考古、材料科学等多领域,可降低扫描成本。

现代考古方法越来越多地依赖三维虚拟表征、计算密集型分析、高分辨率扫描、大规模数据集和机器学习。随着扫描分辨率提高,计算能力、内存和存储文件的问题迅速凸显。高分辨率扫描的处理与分析通常需要内存密集型工作流,大多数计算机无法承担,越来越依赖超级计算机或创新方法在普通计算机上处理。本文提出一种新的小物体大规模微CT扫描协议,采用近乎全自动的处理流程,可在内存受限环境下运行。我们仅用10次微CT扫描即完成1,112个动物骨碎片的扫描,并将其后处理为独立PLY文件。该方法适用于任何能与包装材料区分密度的物体,在古生物学、地质学、电子工程和材料科学等领域均有应用潜力。此外,该方法可立即被扫描机构采纳,整合客户订单以提供更经济的扫描服务。本研究是国际多学科研究联盟AMAAZE(人类学与考古学及动物考古学证据的数学与人类学分析)项目的一部分,该联盟汇聚人类学、数学与计算机科学专家,开发大规模虚拟考古研究新方法。总体而言,本研究的新扫描方法与处理流程为未来大规模高分辨率扫描研究奠定了基础并设定了标准。

原文摘要 · Abstract (English)

Modern archaeological methods increasingly utilize 3D virtual representations of objects, computationally intensive analyses, high resolution scanning, large datasets, and machine learning. With higher resolution scans, challenges surrounding computational power, memory, and file storage quickly arise. Processing and analyzing high resolution scans often requires memory-intensive workflows, which are infeasible for most computers and increasingly necessitate the use of super-computers or innovative methods for processing on standard computers. Here we introduce a novel protocol for en-masse micro-CT scanning of small objects with a {\em mostly-automated} processing workflow that functions in memory-limited settings. We scanned 1,112 animal bone fragments using just 10 micro-CT scans, which were post-processed into individual PLY files. Notably, our methods can be applied to any object (with discernible density from the packaging material) making this method applicable to a variety of inquiries and fields including paleontology, geology, electrical engineering, and materials science. Further, our methods may immediately be adopted by scanning institutes to pool customer orders together and offer more affordable scanning. The work presented herein is part of a larger program facilitated by the international and multi-disciplinary research consortium known as Anthropological and Mathematical Analysis of Archaeological and Zooarchaeological Evidence (AMAAZE). AMAAZE unites experts in anthropology, mathematics, and computer science to develop new methods for mass-scale virtual archaeological research. Overall, our new scanning method and processing workflows lay the groundwork and set the standard for future mass-scale, high resolution scanning studies.

微CT考古自动化3D扫描

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