Unravelling a 17th-century prison escape: The quest to identify the original Hugo Grotius bookchest

In 1621, the humanist Hugo Grotius performed a masterly escape from life imprisonment at Loevestein Castle in the Netherlands by hiding in \na bookchest. Currently, three museums in the Netherlands (Loevestein Castle, Rijksmuseum and Museum Prinsenhof) possess chests related \nto Grotius\xe2\x80\x99 story. This study presents research carried out to decipher whether any of them couldactually claim to have been the one used for the \nescape. Inspection of the materials and structure of the chests allowed us to discard the one in Loevestein Castle from the outset, as it is unlikely \nto have been a bookchest. However, the other two most likely were, and dendrochronological research through digital photographs provided date

Inside out: Fusing 3D imaging modalities for the internal and external investigation of multi-material museum objects

3D imaging methods are increasingly employed in cultural heritage research to analyse and document objects in museum collections. In this work, we provide an interactive visualisation plugin for the open-source software Blender, to combine and inspect two complementary 3D imaging modalities: CT images, which capture the interior; and surface scans, which capture the exterior. 3D CT scan data can be visualised, both as volumetric representation and as orthogonal slices, and a 3D surface scan can be registered onto the CT data. It allows users to simultaneously and interactively inspect these modalities and to virtually cut through an object. It also provides tools for generating output images and videos for research and public outreach purposes. The plugin workflow was applied to four case studies from the collections of the Rijksmuseum, Amsterdam, and the British Museum, London. The plugin is published open-source together with detailed guidelines and a practice dataset

Integrating expert feedback on the spot in a time-efficient explorative CT scanning workflow for cultural heritage objects

Computed Tomography (CT) has proven itself as a powerful technique for analysing the internal structure of cultural heritage objects. The process followed by conservators and technical art historians for investigating an object is explorative: each time a new question is asked based on the outcome of the previous investigation. This workflow however conflicts with the static nature of CT imaging, where the planning, execution and image analysis for a single CT scan can take days, or even weeks. A new question often requires conducting a new experiment, repeating the process of planning, execution and image analysis. This means that the time that is needed to complete the investigation is often longer than originally anticipated. In addition, it brings up more practical challenges such as the transportation of the object, facility availability and dependence on the imaging operator, as well as the cost of running additional experiments. A much needed interactive imaging process, where the user can adapt the CT scanning process based on the insights discovered on the spot, is hard to accomplish. Therefore, in this paper we show how a time-efficient explorative workflow can be created for CT investigation of art objects, where the object can be inspected in 3D while still in the scanner, and based on the observations and the resulting new questions, the scanning procedure can be iteratively refined. We identify the technical requirements for a CT scanner that can address the diversity in cultural heritage objects (size, shape, material composition), and the need for adaptive steering of the scanning process required for an explorative workflow. Our approach has been developed through the interdisciplinary research projects The See-Through Museum and Impact4Art. We demonstrate the key concepts by showing results of art objects scanned at the FleX-ray Laboratory at CWI, Amsterdam

Three line trajectory X-ray tomography datasets of a small wooden block

This submission contains three tomographic datasets of a small wooden block. The data is made available as part of [Bossema et al., 2021]

CT reconstruction and structured light scan of a small wooden block

This submission contains a reconstruction from a tomographic dataset and a structured light scan of a small wooden block. \nThe data is made available as part of [Bossema et al., 2023] and is meant to serve as a practice dataset for the Blender plugin that is published along the article. The code for the plugin can be found here and on github

A line trajectory X-ray tomography dataset of a wooden plank

This submission contains a tomographic dataset of a wooden plank. The data is made available as part of [Bossema et al., 2021]

A CT dataset of a small wooden block

This submission contains a tomographic dataset of a small wooden block