eManuSkript – Digital Palaeography

Seshat: A Digital Measurement Tool for Analysing Medieval Manuscripts

What is Seshat?

According to an apocryphal story, Lord Kelvin or as now believed, Albert A. Michelson, declared in 1900:

“There is nothing new to be discovered in physics now. All that remains is more and more precise measurement.”

Is the fate of palaeography similar? In 1979 the distinguished palaeographer Bernhard Bischoff inadvertently touched on this question when he wrote in the introduction of his handbook that palaeography was being transformed in his time “from an art of seeing and sympathetic understanding” to “an art of measurement” (Paläographie des römischen Altertums und des abendländischen Mittelalters [Berlin, 1979], p. 17). The statement triggered heated reactions and defences of palaeography as an art of cultivated seeing. Our new digital tool Seshat is not intended to promote the idea that palaeography should be a purely quantitative discipline. But it does enable users to measure key features of scripts from high-quality images, which is both useful and desirable in the digital age.

Named after the Ancient Egyptian goddess of scribes, Seshat is a measurement tool with annotation features that make it possible to conduct a thorough palaeographical analysis of a digital object. It allows users to highlight textual regions, underline specific words or lines, insert comments, trace letterforms using adjustable pen angles (0°, 25°, 30°, 50°, and 80°), and excerpt data in different formats to be used as a dataset later. The tracing functionality supports the analysis of script ductus and scribal hand variation.

Taking inspiration from the first version of a software tool for the critical examination of historical handwriting called Graphoskop developed by Maria Gurrado and Giancarlo Lestingi (https://www.irht.cnrs.fr/fr/ressources/sites-web-outils-corpus/graphoskop), we have included a suite of measurement tools that calculate horizontal and vertical distances for particular script and page features: ascender and descender heights, interlinear spacing, margins, overall line heights, and inter-column spaces. A stroke angle measurement feature allows for precise documentation of letterform direction and inclination. Statistical tools automatically calculate averages, standard deviations, and mode values across measurements for both single pages and entire manuscripts.

Seshat is fully IIIF-compatible, enabling users to load manuscript images from major repositories such as the British Library, the Vatican Library, or other IIIF-compliant archives. The option to upload JPEG formatted images is also available. Image cropping functionality is built in, letting users isolate manuscript regions and export these selections in PNG or SVG formats, with or without annotations.

What were our goals when starting to develop this app?

When we started, our main goals were:·To provide a digital tool for precise annotation and measurement of palaeographic features (e.g. ductus, margins, letterforms).

• To simulate traditional palaeographic tracing methods (such as ductus analysis) in a digital environment by including adjustable pen angle tracing.

• To allow users to collect measurable data (distances, angles) and automatically generate statistical outputs to support comparative manuscript studies.

• To enable scholars to manipulate and export parts of manuscript images for publication or focused analysis.

• To ensure integration with IIIF resources for direct access to high-quality manuscript images without requiring local uploads.

Currently, Seshat includes all the functionalities listed above, and is already being applied successfully in internal research for ductus evaluation, scribal variation analysis, and manuscript layout studies.

Seshat in the Future

Seshat is not yet finished. Based on development and user feedback, we plan the following additional features:

Tracing

• Allow users to form strokes with a simulated quill, where the quill size is determined by selecting two points on the canvas in pixels. This size will be adjustable.

• Support saving both individual and clustered strokes together with the underlying cropped manuscript image.

Commenting

• Allow customization of comment text, including font family, font size, and colour, displayed on a transparent layer (removing the current speech bubble design).

• Enable adjustment of text appearance (font, size, colour) for clearer comment placement without obscuring manuscript details.

Measurement

• Integrate tracing and measurement tools to allow for linked analysis (e.g. measuring traced strokes).

• Provide pixel-based measurements that can be converted to standard units.

• Enable curve measurement and potentially measure nib (quill) width directly from the stroke trace data.

Alphabet selection

• Develop an alphabet selection tool to extract individual letter shapes defined by the user.

Moving forwards, we will be improving Seshat based on user feedback and will be doing our best to deliver a very user-friendly interface by spring 2026!

— Project eManuSkript Team

Proteus: A Tool to Simplify Post Processing of Multispectral Images

In manuscript studies, scholars often encounter texts that are barely legible from centuries of damage, reuse as in the case of palimpsests, faded ink, or chemical reactions. Multispectral Imaging (MSI) has emerged as a way to recover such hidden texts, capturing images of manuscripts under different wavelengths of light to reveal what the naked eye can no longer perceive.

While MSI is a successful and useful technique for text recovery, the tools required to process MSI images are often intimidating. Many existing applications assume a high degree of technical knowledge, from a chemical literacy to skills in navigating dense software menus. This steep learning curve can be a barrier for students and researchers who are new to the field.

A Tool for Everyone

Our goal was to develop a lightweight app with a simple, intuitive interface that enables users—especially those without a technical background—to explore MSI data without coding. We envisioned Proteus not just as a tool, but also as a guide: something that helps users navigate MSI post-processing with ease, without becoming imaging experts, by giving simple instructions on what images or features should be used for certain scans.

Instead of offering dozens of rarely-used features, Proteus focuses on a few impactful tools, delivered through a simple interface. We designed the interface so that each function is explained via pop-up tips, recommends effective image combinations for different tasks, performs the heavy computations silently in the background, and is supported by our MSI tutorials for a better understanding of the whole process. Our aim was to allow scholars to focus on interpreting texts, not on configuring software.

Simple and Sustainable Design

Proteus is built in Python, using libraries like OpenCV, NumPy, Pillow, and tkinter. This combination allows us to offer real-time image processing inside a platform-compatible graphical user interface. The GUI, powered by tkinter, makes image enhancement accessible through point-and-click interactions— which comes in handy for users with humanities backgrounds.

Users can load certain image stacks taken using multispectral imaging systems into the app, choose which feature to use, and select bands for further processing.

Among Proteus’s core features are:

– Pseudo-color images, which enhance contrast by combining spectral bands as RGB channels.

– Principal Component Analysis (PCA), which mathematically isolates features that reveal faded or overwritten text.

– Power, which intensifies each pixel in the image to get a better result, especially on faded pages.

These enhancements are powered by matrix operations (via NumPy) and OpenCV functions for tasks like histogram equalization, resizing, and denoising. Proteus also follows standardized naming conventions for exported images, and delivers a text file with the metadata, including a record of used features. This makes it easy to manage results across projects.

The app’s modular code design ensures future extensibility—whether for supporting more spectral formats, integrating machine learning, or adding new filtering methods.

The Current Version of Proteus

The first working versions of Proteus have already been actively used the app in internal projects and tasks. Following evaluations with Dr. Anna Dorofeeva and Dr. Alexander Zawacki, and with the assistance of our MSI team, we’ve gathered valuable feedback—pinpointing both bugs and areas for improvement.

This feedback is now shaping Proteus v3.0, which will feature improved performance, bug fixes, and new features inspired by user experience. We’re also excited about early experiments using Proteus on non-MSI images, where enhancements like PCA and contrast filtering have revealed details even in ordinary scans.

What Next?

Proteus is built in accordance with the principle that digital manuscript tools should be clear, simple, and powerful. We want to minimise the time spent on post processing and allow researchers to make the best use of their time.

We intend for Proteus to become a standard teaching and research tool in digital humanities programs, especially in MSI training units. By simplifying complex workflows, it will lower the barrier for students and scholars – even those with limited technical skills – to engage with multispectral imaging.

As the field of manuscript studies embraces new technologies, we believe tools like Proteus can lead the way—quietly doing the heavy work, while putting discovery back in the hands of the user.

References

Conjeti, Sailesh, Stefanie Demirci, and Vincent Christlein. Image retrieval in big image data. Elsevier, 2023.

DigiTRiP-Redaktion (17. Februar 2025). Proteus – Handschriftengeheimnisse aufdecken. DigiTRiP. Abgerufen am 26. Mai 2025 von https://doi.org/10.58079/13bto

Knox, Keith. “Hoku Software .” Rochester Institute of Technology, 11 Sept. 2017.

Leslie’s Blog. “Gradual Gaussian Blur Using Opencv.” Leslie’s Blog, 5 Aug. 2020, leslietj.github.io/2020/08/05/Gradual-Gaussian-Blur-Using-OpenCV/.

Roepke, Brian. “The Magic of Principal Component Analysis through Image Compression.” Lambda with Text - Wide, Data Knows All, LLC, 22 Mar. 2024, dataknowsall.com/blog/imagepca.html.

Team, PlantCV Development. “Pseudocolor.” PlantCV, plantcv.readthedocs.io/en/latest/visualize_pseudocolor/

eManuSkript: New project to create digital teaching tools in palaeography funded at the University of Göttingen

Group of people sitting around a round table in the middle of a room filled with bookcases. — Göttingen students working with manuscripts at the Vercelli Spring School.

A project by Dr. Anna Dorofeeva at the Institute for Digital Humanities in Göttingen has recently been awarded €400,000 in the Freiraum 2023 competition by the Stiftung Innovation in der Hochschullehre. Over the next two years, a team of historians and programmers, working in close collaboration with BA and MA students, will develop a range of teaching and learning tools for manuscript studies, including palaeography.

There exist very few digital tools suitable for teaching the full range of skills necessary for working with medieval codices. Access to culturally important manuscript sources is restricted to those with specialized subject knowledge, which creates significant challenges for students. In addition, the immense potential of the millions of manuscript images available in interoperable IIIF format has yet to be fully exploited in teaching. This project aims to develop a series of digital tools that will make use of these images and of the expertise available in Göttingen. The tools will include apps for measuring, selecting and modifying scripts; evaluating page layout; and working with manuscript bindings. Other apps and extensive tutorials are planned. The project will also undertake further development of pre-existing tools, including improvements to applications for multispectral imaging, for digital editing and annotation, and for forms of image storytelling. Guided student participation will be key to the development of these tools, which means that they will be rooted in practical requirements, conceived by the users themselves, and suitable for both classroom and research use.

The eManuSkript project runs for two years from 1 April 2024. A website with more information is being developed. In the meantime, please get in touch with the team members if you have any questions or if you wish to collaborate.