Lost Visions: retrieving the visual element of printed books from the nineteenth century

我们的时代是一个图像以前所未有的速度激增的时代，得益于数字技术。因此，具有讽刺意味的是，我们过去的视觉文化正受到同样的技术进步的严重威胁。现在许多口头文本都是由机器存储和传递的，数字搜索技术帮助我们理解这些文本的含义、来源和接受程度。然而，出于经济或复杂的知识产权问题的原因，这些文本中的插图经常被省略。当它们被纳入时，它们的质量往往很低，并且没有理解它们所需的元数据。虽然它们的市场价值几乎不会因为这些缺点而受到影响，但它们作为审美、文学和历史信息来源的使用却严重受损。即使研究表明，插图文本的性质、意义和策略与未插图的文本截然不同，甚至与去除图像的相同语言文本的性质、意义和策略截然不同，但明天的读者可能几乎不会意识到插图。艺术、教育和信息产品的整个流派实际上可能对我们来说已经失去了。大英图书馆拥有的一个数据集提供了一个开始解决这个问题的独特机会。此数据集包含68,000个数字化卷(约2500万页)，涵盖了漫长的十九世纪的文学、哲学、通史和地理学，这一时期可以说是英国书籍插图中最重要的时期。在这些年里，生殖技术的快速变化与艺术的含义和接受程度的变化是同步的。艺术民主化了，书籍插图变得比以往任何时候都更具收藏价值和流动性。数据集中的页面以高分辨率扫描并进行OCR，并注意到其中存在非语言对象。我们将使用计算方法来识别这些非语言对象的视觉特征(即它们是否参与了地图、图表、表格、图形、重要排版等的性质)。我们的目标是通过提供这本书的完整参考书目细节，图像的确切位置和大小，以及可能的情况下，标题或标题，以及艺术家来增加可用的元数据。此外，我们将开发工具，以确定图像的再利用(以复制品、重绘、重写和转载的形式)。其结果将是一个基于网络的界面，提供对图像数据库的可搜索访问以及伴随的元数据。因此，这个项目将挽救大量的图像，否则这些图像将在所有目的和目的上丢失。虽然拨款的规模不足以对这些插图的主题进行全面分析，但我们将试验分配标签的众包方法。我们目前正在与一家数据管理SME讨论如何通过协作来大规模提高语义标记的效率并降低单位成本。这是一个本身很大的项目，但其最终影响要大得多。它有可能改变人们对插图的理解和重视，为渴望图像的商业世界提供插图素材，并导致在大型数据库中对图像进行更准确的分类和分析。为了处理项目期间出现的问题，并实施远远超出项目范围的影响战略，我们成立了一个由大量合作者和外部顾问组成的小组，他们拥有项目本身的专业知识，并在潜在用户的世界中具有专业知识和影响力。

Ours is an age when images proliferate at unprecedented speed thanks to digital technology. So it is ironic that our past visual culture is seriously threatened by the very same technical advances. Many verbal texts are now stored and delivered by machine, and digital search techniques help us understand the meaning, provenance and reception of these texts. However, for reasons of economy or of complex IPR issues, the illustrations in these texts are frequently omitted. When included, they are often of low quality and without the metadata which are needed for understanding them. While their market value hardly suffers because of these shortcomings, their use as sources of aesthetic, literary and historical information is seriously compromised. There is a risk that tomorrow's readers will be almost unaware of illustration, even though research has shown that illustrated texts have qualities, meanings and strategies which are very different from those of texts that are not illustrated, and even strikingly different from those of the same verbal texts stripped of their images. Whole genres of artistic, educational and informative products may effectively be lost to us.A unique opportunity to start addressing this issue is provided by a dataset held by the British Library. This dataset consists of 68,000 digitised volumes (approx. 25 million pages) covering 'Literature', 'Philosophy', 'General History' and 'Geography' from the Long Nineteenth Century, a period that is arguably the most important in British book illustration. In these years, rapid changes in reproductive techniques were paralleled by changes in the meanings of art and its reception. Art was democratised and book illustrations became more widely collectable and mobile than ever before. The pages in the dataset are scanned at high resolution and OCR'd and the presence of non-verbal objects found in them is noted. We will use computational methods to identify the visual characteristics of these non-verbal objects (i.e. whether they partake of the nature of maps, diagrams, tables, graphs, significant typographic layout etc.). We aim to add to the available metadata by giving full bibliographical details of the book, the exact location and size of the image, and, where possible, a caption or title, and an artist. In addition, we will develop tools for identifying the re-use of images (in the form of reproductions, re-drawings, recuttings and transmediations). The result will be a web-based interface that provides searchable access to a database of images with accompanying metadata. As such, this project will rescue large numbers of images which would otherwise to all intents and purposes be lost. While the size of the grant does not allow for a full analysis of the subject matter of these illustrations, we shall trial crowd-sourcing methods for assigning tags. We are currently in discussion with a data management SME on how collaboration could increase the effectiveness and decrease the unit cost of semantic tagging on a large scale. This is a project big in itself, but far bigger in its eventual impact. It has the potential to revolutionise how illustration is understood and the importance accorded to it, to supply an image-hungry commercial world with illustrative material, and to lead to ever more accurate ways of classifying and analysing images in large databases.To deal with issues which arise during the project and to implement an impact strategy which will be felt well beyond it, we have set up a substantial panel of collaborators and external advisers who have expertise in the project itself and both expertise and influence in the world of potential users.