For about 2000 years, no paper was used as a media in China but writings and drawings were captured on bamboo and wooden slips. Several slips were bound together with strips and rolled up to a scroll. The writings and drawings were either brushed or even carved into the wood. Those documents are very precious for culture inheritance and research, but due to aging processes, the discovered pieces are sometimes in a poor condition and also soiled. Because cleaning the slips is not only challenging but also writings could be erased, we developed a method to digitize such historical documents without the need of cleaning. We perform a 3-D X-ray micro-CT scan resulting in a 3-D volume of the complete document. With our approach, we were able to investigate the scroll without any manual labor (e.g. unwrapping or cleaning). We showed that the method also works for heavily soiled scrolls where nothing is readable with the naked eye. This can help conservators to store all writings before they may be erased by the cleaning process. Finally, we present a manual technique to virtually unwrap and post-process the documents resulting in a 2-D image of all bamboo slips.

Corruptions such as aging-processes or moisture make it often impossible to digitize historical books or scrolls with common digitization approaches. 3-D X-ray CT is a non-destructive method which can provide a look inside those documents. Current CT scans use a full-circle trajectory with a large number of projections and high exposure times. However, there are historical goods that may suffer from high radiation dose. In this work, we present an evaluation of a 3-D X-ray CT scan with three reduced projection sizes reconstructed with four common algorithms compared to the mentioned high dose approach. For our experiments, we used a book with 22 pages and a leather cover. Every page has writings made with iron gall ink. We show that we can reduce the number of projections by at least 85 and up to 92.5 percent without severe loss of information on the book’s writings. The reconstructed volumes are compared with regard to common similarity measures as well as visual outputs of a selected 2-D mapped page.

A method analysing the local variations of a series of CT measurement s to determine the single point noise is presented. Using a realistic simulation model of the CT system, the mean local offset and he single point uncertainty can additionally be estimated. The method is tested on a measurement series of a micropart. It is s hown that the method is capable of identifying areas of increased uncertainty caused by artefacts and of quantifying the value of the single point uncertainty. Additionally, the method is validated using an existing method that is capable of assessing the local quality of a CT measurement.

Up to now, the only standardized method to determine the measurement u nc rtainty for computed tomography (CT) is to use calibrated workpieces as specified in the guideline VDI/VDE 2630 Part 2.1 . This paper discusses a promising numerical method for uncertainty determination with help of a virtual metrological CT (VMCT). It gives an explanation of the adjustments, the input parameters and the execution of the simu lation. Furthermore, it discusses the first results of uncertainty determination compared to the method of using calibrated workpieces with t he aid of two example cases.

Artefacts within CT volume data have a large impact on the results of dimensional measurements. To avoid measurement deviations, it is therefore crucial to identify regions affected by artefacts. The presented method analyses the volume data in the proximity of an extracted surface point to calculate a Local Quality Value (LQV). Using this method, surface points affected by artefacts are iden tified and highlighted in 2D and 3D visualisations. As only the volume data and the extracted surface are req uir d to calculate the LQV, no additional knowledge like a CAD model or a reference measurement is necessary and the analysis can be carried out automatical ly. CT scans of calibrated gauges blocks that exhibit large errors in the s egmented surface dataset due to artefacts are used to demonstrate the capability of the presented method. It is shown that it is possible to increase the accuracy of dimensional measurements by considering the i formation provided by the LQV.