Contributions to computer-aided analysis of cuneiform tablet fragments
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Date
2019
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Abstract
This thesis presents methods for computer-aided three-dimensional analysis of digitized
cuneiform tablets, an ancient type of writing documents. Since cuneiform script is predominantly
conserved in the form of fractured clay tablet fragments, identifying matching fragments
is a central task of manuscript reconstruction. This goal can benefit from the increasing
3D digitization of cuneiform fragments, which offers access to highly accurate cuneiform
representations.
The main contribution of the thesis is a novel model-based method for the extraction of
individual cuneiform wedges and associated wedge geometries from 3D scans, which can serve
as a base for a statistical analysis of script features. This new automated approach enables
access to large amounts of accurate quantitative cuneiform script features, which were not
accessible by previously available 2D methods and can be employed for script similarity-based
identification of candidates for fragment joining. A central aspect and challenging task is the
robustness of the presented extraction method against scanning issues and mesh errors. This
is achieved by employing a watershed-based wedge area extraction operating on a surface
distance field with a subsequent constructive multi-stage model fitting. The extracted wedge
models are refined by a wedge type classification followed by an effective wedge validation to
handle false detections on fracture faces and damaged surfaces. An evaluation with respect to
extraction rates, robustness, and performance shows the suitability of the developed methods
that goes beyond an application purely for cuneiform fragment joining.
To address some compromises made during the wedge extraction regarding the representation
of complex features, a fast supplementary approach for extracting skeletal surface features
is presented. These features provide an alternative readable cuneiform representation and
are created using a thinning approach on an approximated distance field. The quality of the
resulting skeletons is optimized by employing a complex junction resolution, branch pruning
and branch simplification methods, where both pruning and simplification can be used to
adjust the resulting representation to different use cases. Aside from manual feature analysis,
possible application scenarios also include providing a representation that can be handled by
GraphCNNs for retrieval related tasks on cuneiform structures.
The cuneiform segmentation methods are complemented by a set of visualization concepts for a
cuneiform segmentation framework. This includes a hierarchical concept for data handling and
persistent storage of the generated segmentation data. Beyond, methods for fast rendering of
large meshes, visualization methods to achieve good depth perception, detail enhancement, and
semi-realistic surface shading are integrated. In order to not only address application scenarios
like fragment joining and collation related tasks, the framework provides a sophisticated,
highly interactive, and flexible segmentation data visualization that additionally offers fast
geometry selection methods. A good accessibility of the generated data is guaranteed though
an XML-based file format for storing segmentation data and through providing flexible data
export methods. Although the framework is primarily intended for real-time segmentation,
most segmentation methods can also be scheduled to process large numbers of fragments
without user interaction.
All presented methods are evaluated with respect to performance aspects and their suitability
for a set of philological use cases. The developed methods can be used flexibly in the scope of
many aspects of the investigated application cases. This does not only apply to the automated
feature extraction, but also to manual analysis aspects, which were discovered only by the
new availability of the methods. The usability of the framework is underlined by the fact that
it is actively being used by philologists from the Hethitologie-Portal Mainz, an established
online resource in Hittitology.
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Keywords
Cuneiform, Geometry processing, Mesh segmentation, Wedge extraction, Statistical script analysis, Segmentation framework