Calibration of Digital Image Analysis Protocols for Archaeological Ceramics

考古陶瓷数字图像分析协议的校准

基本信息

  • 批准号:
    1005992
  • 负责人:
  • 金额:
    $ 13.97万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2010
  • 资助国家:
    美国
  • 起止时间:
    2010-08-15 至 2014-07-31
  • 项目状态:
    已结题

项目摘要

With National Science Foundation support, Dr. Chandra Reedy and an interdisciplinary team of students at the University of Delaware will develop and test new procedures for using inexpensive light microscopes to better understand ceramics, one of the most archaeologically-significant classes of materials. They will modernize the technique of thin-section petrography, which uses small samples mounted on a glass slide and ground down to 30 microns thick. When examined under a microscope with polarized light, minerals in such samples are identifiable by optical properties. Thin-section petrography is used to characterize archaeological ceramics and investigate ceramic production, function, exchange, technological style, and use history. However, the technique is often marginalized because of some challenges. For example, traditional methods of obtaining quantitative data from thin sections are very time consuming, but using only qualitative data limits usefulness. Digital image analysis has potential to alleviate these problems. However, some fundamental experimental work is needed first with laboratory-prepared standards of known composition. To ensure reliability of analyses of archaeological ceramics of unknown original recipes, protocols first must be tested for accuracy with laboratory-prepared specimens having additives of known composition, size, and amount, and fired under known conditions.The primary focus of this research, then, is to calibrate protocols for analysis of digital images of thin sections viewed under a polarizing microscope. Additional experiments will use images obtained by scanning whole thin sections under low magnification. An advantage is that these images include the entire area of the thin section rather than just a single field of view as under a microscope, facilitating macrotexture studies. Some exploratory work also will involve digital images of sherds themselves, to obtain quantitative data that supplements thin-section studies. An advantage is that the time and expense of thin-section cutting, mounting, and grinding are eliminated, allowing data to be collected on even larger numbers of specimens for rapid characterization of some features of a sherd.For all three of these approaches, using laboratory-prepared specimens as known standards is crucial for development of reliable protocols. In the final phase of research the protocols will be applied to archaeological specimens that have already been well characterized by relevant comparative techniques of analysis. Applying the finished protocols to archaeological samples will allow editing, refinement, and clearer explanations where needed so that the protocols are more widely usable and reproducible.The intellectual merit of this research is that it will result in new, modernized procedures for quantitative polarized light microscopy of ceramics. The broader impact of the study is that ceramic materials are found at archaeological sites throughout the world. These materials represent objects of a wide range of functions and serve as important markers for understanding many cultural issues about the past. This research will provide the basis for new methods of analyzing and understanding these materials, so that questions about humanity's past can be explored more fully. Students from several disciplines will participate in the project to enhance their laboratory training and ability to work together across different fields while increasing their knowledge about ceramics, one of the most important cultural materials in human history.
在国家科学基金会的支持下,钱德拉·里迪博士和特拉华州大学的一个跨学科学生团队将开发和测试使用廉价光学显微镜的新程序,以更好地了解陶瓷,这是最具考古意义的材料之一。他们将使薄片岩相学技术现代化,该技术使用安装在载玻片上的小样品并研磨至30微米厚。当在显微镜下用偏振光检查时,这些样品中的矿物可通过光学性质识别。薄片岩相学用于表征考古陶瓷,并调查陶瓷生产,功能,交换,技术风格和使用历史。然而,由于一些挑战,该技术往往被边缘化。例如,从薄切片获得定量数据的传统方法非常耗时,但仅使用定性数据限制了有用性。数字图像分析具有缓解这些问题的潜力。然而,一些基本的实验工作,首先需要与实验室制备的已知组成的标准。为了确保可靠性的考古陶瓷的分析未知的原始配方,协议首先必须进行测试的准确性与实验室制备的标本具有已知的成分,大小和数量的添加剂,并在已知的条件下烧制。本研究的主要重点,然后,是校准协议的数字图像分析薄切片偏光显微镜下观看。其他实验将使用通过在低放大倍数下扫描整个薄切片获得的图像。一个优点是这些图像包括薄切片的整个区域,而不是像显微镜下那样只有一个视场,便于宏观纹理研究。一些探索性工作还将涉及碎片本身的数字图像,以获得补充薄片研究的定量数据。其优点是,无需进行薄片切割、镶嵌和研磨,从而可以在更大量的样品上收集数据,以快速表征碎片的某些特征。对于所有这三种方法,使用实验室制备的样品作为已知标准对于开发可靠的协议至关重要。在研究的最后阶段,协议将适用于考古标本,已经很好地表征了相关的比较分析技术。将完成的协议应用于考古样品将允许编辑,细化,并在需要时更清晰的解释,使协议更广泛地使用和reproducible.The这项研究的智力价值是,它将导致新的,现代化的定量偏振光显微镜的陶瓷程序。这项研究的更广泛的影响是,陶瓷材料在世界各地的考古遗址中被发现。这些材料代表了广泛的功能对象,并作为了解过去的许多文化问题的重要标志。这项研究将为分析和理解这些材料的新方法提供基础,以便更充分地探索有关人类过去的问题。来自多个学科的学生将参加该项目,以提高他们的实验室培训和跨不同领域合作的能力,同时增加他们对陶瓷的知识,陶瓷是人类历史上最重要的文化材料之一。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Chandra Reedy其他文献

Chandra Reedy的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Chandra Reedy', 18)}}的其他基金

U.S. China Planning Visit: Roots of Technological Innovation and Change in Ceramic Traditions of Sichuan Province
美国中国计划访问:技术创新和四川陶瓷传统变革的根源
  • 批准号:
    1339530
  • 财政年份:
    2013
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Standard Grant

相似国自然基金

超灵敏高分辨的Digital-CRISPR技术用于免扩增的多重核酸检测
  • 批准号:
  • 批准年份:
    2021
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
基于Digital Twin的数控机床智能运行维护方法研究
  • 批准号:
    51875323
  • 批准年份:
    2018
  • 资助金额:
    60.0 万元
  • 项目类别:
    面上项目
基于数字PCR(digital-PCR)技术的耳聋无创产前检测研究
  • 批准号:
    LQ19H040016
  • 批准年份:
    2018
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
基于Digital LAMP技术的循环肿瘤细胞检测和分型新方法研究
  • 批准号:
    81702102
  • 批准年份:
    2017
  • 资助金额:
    20.0 万元
  • 项目类别:
    青年科学基金项目
基于表面工程的外泌体digital PCR定量分析体系的构建及转化医学研究
  • 批准号:
    81702959
  • 批准年份:
    2017
  • 资助金额:
    10.0 万元
  • 项目类别:
    青年科学基金项目

相似海外基金

3D Camera-based Digital Image Correlation for Tissue Characterisation in Robot-Assisted Surgery
基于 3D 相机的数字图像相关,用于机器人辅助手术中的组织表征
  • 批准号:
    2894727
  • 财政年份:
    2023
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Studentship
AI-empowered 3D Computer Vision and Image-Omics Integration for Digital Kidney Histopathology
AI 赋能的 3D 计算机视觉和图像组学集成用于数字肾脏组织病理学
  • 批准号:
    10635439
  • 财政年份:
    2023
  • 资助金额:
    $ 13.97万
  • 项目类别:
Creating a Technological Infrastructure for the Digital Restoration of Cultural Properties Using Statistical Image Processing and Deep Learning
利用统计图像处理和深度学习为文化财产数字化修复创建技术基础设施
  • 批准号:
    22H00748
  • 财政年份:
    2022
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Wide-area, high-resolution digital image analysis for neurodegenerative diseases
神经退行性疾病的广域高分辨率数字图像分析
  • 批准号:
    22K15214
  • 财政年份:
    2022
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Digital Image Correlation Analysis for Pseudo-superplastisity of Mg alloys
镁合金拟超塑性的数字图像相关分析
  • 批准号:
    22K04771
  • 财政年份:
    2022
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Development and utilization of digital / analog teaching materials using 3D image processing and 3D printers for biological education
利用3D图像处理和3D打印机进行生物教育的数字/模拟教材的开发和利用
  • 批准号:
    22K02988
  • 财政年份:
    2022
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Development of digital image enhancement method aimed at improving visibility for elderly persons
开发旨在提高老年人能见度的数字图像增强方法
  • 批准号:
    22K12097
  • 财政年份:
    2022
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Establishing a technical basis for statistical image processing and deep learning for the digital restoration of cultural heritage.
为文化遗产数字修复的统计图像处理和深度学习奠定技术基础。
  • 批准号:
    22K18496
  • 财政年份:
    2022
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Grant-in-Aid for Challenging Research (Exploratory)
Digital Image Correlation (DIC) System for Assessment of Critical Infrastructure and Digital Twin
用于评估关键基础设施和数字孪生的数字图像相关 (DIC) 系统
  • 批准号:
    RTI-2023-00102
  • 财政年份:
    2022
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Research Tools and Instruments
Deep Learning and Interpretability in Digital Image Forensics
数字图像取证中的深度学习和可解释性
  • 批准号:
    RGPIN-2022-03049
  • 财政年份:
    2022
  • 资助金额:
    $ 13.97万
  • 项目类别:
    Discovery Grants Program - Individual
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了