Digital approaches to the capture and analysis of watermarks using the manuscripts of Isaac Newton as a test case

使用艾萨克·牛顿的手稿作为测试用例来捕获和分析水印的数字方法

• 批准号: AH/V009486/1
• 负责人: Scott Mandelbrote
• 金额: $ 25.82万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=AH%2FV009486%2F1
• 关键词: Digital; approaches; capture; analysis; watermarks

This project will investigate two research areas with general application in digital humanities scholarship, using the dispersed manuscript corpus of Isaac Newton as a test case. The immediate purpose of the test case will be to use artificial intelligence to assist with the identification and classification of watermarks in Newton material and, in the process, to build a general tool to assist with the organisation and dating of manuscripts. The project also has much wider significance. The project's first stage will be the methodological investigation of techniques for the production of images of watermarks which are suitable for automated analysis, using both new photography and the exploration of the potential latent in existing images. During the second stage, we will develop computer vision methods to systematically cluster and match the assembled corpus of watermark images across manuscripts and collections. Methods developed through this project will be transferrable to watermark collections beyond that of Newton's corpus, creating a methodology for scholars seeking to analyse, date, and organise historical collections via watermark matching, and for conservators seeking to establish standardised surveying and documentation methods while imaging and digitising watermarked documents. A final stage of the project will allow us to disseminate our findings through research workshops, web tools, and improvements to online databases, as well as traditional publications in journals.Since the groundbreaking early twentieth-century research of Charles Moïse Briquet, watermarks have formed a central part in the dating of otherwise undated manuscripts. Briquet's monumental 1907 catalogue, Les filigranes, made it possible, in principle, to date (and to some extent localise) pre-1600 watermarks found by researchers in manuscripts by reference to exemplars in Briquet's catalogue. While this catalogue and others have been digitised thanks to the Bernstein consortium (https://memoryofpaper.eu/), advances in research and technology have revealed the limitations of the traditional approach, which requires time-consuming procedures and some degree of expertise for the identification of each single watermark. It is very difficult to find exact matches between watermarks in situ and those reproduced in any catalogue, first due to the limited comprehensiveness of the catalogues, and, second, because each individual watermark is produced in two "twin" versions, never perfectly identical, and suffers deformation over time as a result of repeated use in the paper manufacturing process. By developing and enhancing new approaches and techniques to improve the acquisition and analysis of watermarks, we hope to solve basic problems and thereby provide benefit to all who must rely upon paper documents for chronological evidence. While computer vision has made significant progress in recent years thanks to machine learning and artificial intelligence, this project will build on cutting-edge work already undertaken by the Ecole Nationale des Chartes and its partners (notably the computer scientists at École des Ponts ParisTech) to investigate the problem of matching images, specifically of watermarks, across formats (photographs and tracings). In creating a corpus of images used to train and develop the open source software created by the Ecole des Chartes we will build on recent work by The National Archives (TNA) to use comparatively affordable equipment and techniques to produce images of watermarks that are highly suitable for machine analysis. The project will develop and apply both of these approaches in order to attempt to enhance the computer-vision software so that it may be able to unlock the latent information held in thousands of existing images shot in reflected light which institutions have already digitised and made accessible through IIIF.

该项目将使用艾萨克·牛顿分散的手稿语料库作为测试用例，研究数字人文学术中普遍应用的两个研究领域。该测试用例的直接目的是使用人工智能来协助识别和分类牛顿材料中的水印，并在此过程中构建一个通用工具来协助手稿的组织和约会。该项目还具有更广泛的意义。该项目的第一阶段将是对适合自动分析的水印图像制作技术进行方法学研究，同时使用新的摄影技术和探索现有图像的潜力。在第二阶段，我们将开发计算机视觉方法，以系统地聚类和匹配手稿和收藏中组装的水印图像语料库。通过该项目开发的方法将可应用于牛顿语料库之外的水印收藏，为寻求通过水印匹配来分析、年代和组织历史收藏的学者，以及寻求在对水印文档进行成像和数字化时建立标准化测量和记录方法的保护者创建一种方法。该项目的最后阶段将使我们能够通过研究研讨会、网络工具和在线数据库的改进以及期刊中的传统出版物来传播我们的发现。自从查尔斯·莫伊兹·布利奎特 (Charles Moïse Briquet) 二十世纪早期的开创性研究以来，水印已成为对其他未注明日期的手稿进行约会的核心部分。 Briquet 1907 年的纪念性目录《Les filigranes》原则上使得研究人员参考 Briquet 目录中的范例在手稿中发现的 1600 年之前的水印得以确定日期（并在一定程度上本地化）。虽然该目录和其他目录已在伯恩斯坦联盟 (https://memoryofpaper.eu/) 的帮助下实现数字化，但研究和技术的进步揭示了传统方法的局限性，传统方法需要耗时的程序和一定程度的专业知识来识别每个水印。很难找到原位水印与任何目录中复制的水印之间的精确匹配，首先是因为目录的全面性有限，其次是因为每个单独的水印都是以两个“双胞胎”版本制作的，永远不会完全相同，并且随着时间的推移，由于在造纸过程中重复使用而会变形。通过开发和增强新的方法和技术来改进水印的获取和分析，我们希望解决基本问题，从而为所有必须依靠纸质文档获取时间证据的人带来好处。尽管计算机视觉近年来在机器学习和人工智能的帮助下取得了重大进展，但该项目将建立在法国国立图表学院及其合作伙伴（尤其是巴黎高科理工学院的计算机科学家）已经开展的前沿工作的基础上，研究跨格式（照片和描画）的图像匹配问题，特别是水印匹配问题。在创建用于训练和开发由法国皇家特许学院创建的开源软件的图像语料库时，我们将在国家档案馆 (TNA) 最近的工作基础上，使用相对便宜的设备和技术来生成非常适合机器分析的水印图像。该项目将开发和应用这两种方法，以尝试增强计算机视觉软件，使其能够解锁数千张在反射光下拍摄的现有图像中的潜在信息，这些图像机构已经数字化并可通过 IIIF 访问。

项目成果

The Newton Project

牛顿计划

• 发表时间: 2022
• 期刊: European Mathematical Society Magazine
• 作者: Mandelbrote, S.

Chasing the Clues in Isaac Newton's Manuscripts

在艾萨克·牛顿的手稿中寻找线索

• 发表时间: 2021
• 期刊: Science History Institute
• 作者: Voelkel, J. R.