Session 17 — Imaging the Artefact
Saturday 11:30 - 13:00
Chair: Katherine Rogers
Knowledge in Surface Details: Reflectance Transformation Imaging for Studying and Preserving Medieval Manuscripts
University of Kentucky
Conventional photography does not capture surface details well. Generally, photographers attempt to minimize variations, like shadows, which could reveal such details. When variations occur, photographers tend to mitigate them through post-processing techniques—like flat-field correction. However, surface details hold invaluable information. In the case of medieval manuscripts, many contain dry-point glosses. These glosses are notoriously difficult to see. By design, they are made to go unnoticed, etched with a stylus but no ink. To view them requires an acute angle to the surface of the page and aid from a raking light—conditions antithetical to conventional photography. Developed to capture and highlight surface detail, Reflectance Transformation Imaging (RTI) generates a composite image from a series of photographs taken with varied directional lighting, revealing difficult to see features like dry-point glosses and other surface details.
In my talk, I will discuss uses of RTI to capture surface details in the 8th-century St Chad Gospels. These details include dry-point glosses and the state of the manuscript's pigments. RTI has generally been used to capture the likes of carved stones, cuneiform tablets, brick stamps, wall paintings, and small artifacts, like coins. As I will demonstrate, RTI has great benefits for capturing, studying, and preserving manuscripts. For instance, scholars studying dry-point glosses regularly report uncertainty as to a gloss' content. The composite images generated by RTI eliminate much of this uncertainty. Furthermore, RTI reveals vital information about the state of a manuscript's pigments, especially a manuscript such as the St Chad Gospels in which its artists layered pigments. When compared with a series of conventional photographs taken over time, visual information from RTI provides benefit for mapping the aging process of a manuscript.
Textiles and Data: Application of Computer Vision to Cross Collection Characterisation of Historic Silk Textiles
University of Birmingham
This paper presents the results of my PhD research which applies computer-based imaging technologies to examine historic silk production evidence. My program combines high-resolution images with a computer vision software application to measure identifiable quality and workshop characteristics for weft-faced compound weave figured silks attributed to Mediterranean workshops between ca. AD 600-1200.
For a variety of reasons, research for this category of textiles has slowed in recent years. While essential to protect fragile textiles from damage, the consequence of conservation standards has been reduced collections access. Resource constraints and changes in museum practices mean that many institutions now focus on exhibitions rather than research. At some institutions, large textile collections built up on the heels of the antiquarian era now languish. Even at well-resourced institutions, there is little opportunity for research.
Dramatic advances in digital imaging provide opportunities for the development of new methods for investigation and documentation. My research protocol combines a research grade digital microscope with a custom-built stage to perform precise digital ‘sampling’ for measurement of textile attributes including yarn characteristics, textile structure, density and pattern unit features. The computer vision application aids in error detection, providing a form of ‘industrial inspection’ for ancient textiles. The outcome is a set of objective and reproducible measurements enabling specific comparison of attributes across different collections.
By using my portable equipment setup, I was able to record 125 silk fragments in ten different collections in North America and Europe. Analysis demonstrates patterns of work practices and imitative pattern reproduction among workshops. Results also help to re-unify textiles divided in antiquity or after excavation. In the future, this methodology could provide the basis for a shared database of images available to a broader community of researchers as well as supporting the work of conservators.
University of Leeds
The recording of ornamental motifs in anthropological and archaeological contexts tends to assign class types with specific relevance to the motif within a single, or small related group of, cultural and material contexts. There is potential in creating digital records of certain ornamental forms to describe motifs essentially as an uninterpreted shape, for example as a sequence of coordinates. This approach is considered to be particularly applicable to geometric motifs, for example in the context of prehistoric mark making. The digitisation of ornamental motifs in this manner allows them to be stored and transmitted in a manner which is efficient in memory usage and which is convenient for measurement allowing the reanalysis and reuse of data. The storage of descriptions of ornament in numerical format also makes them amenable to bottom up classification systems derived through cluster analysis or neural networks rather than assigning potentially culture or context specific type groupings.
This paper will describe, as a case study, a method designed for the comparison of spiral motifs and will discuss how the classifications derived from numerical description differ from those based on the mathematical equations of spirals which have commonly been used to assign class groups to decorative spirals. Finally, this paper will discuss the potential for making publicly accessible both the data collection method and the data themselves through online databases. This would make accessible a large and augmentable body of data from which ornament could be visually reconstructed making it accessible for qualitative analysis and providing shape descriptions in a manner which is convenient for a wide range of quantitative analyses.