GigaMesh and Gilgamesh 3D Multiscale Integral Invariant Cuneiform Character Extraction
- Title
- GigaMesh and Gilgamesh 3D Multiscale Integral Invariant Cuneiform Character Extraction
- Creator(s)
- Mara, Hubert
- Krömker, Susanne
- Jakob, Stefan
- Breuckmann, Bernd
- Date
- 2010
- Is Part Of
- Proceedings of the VAST: Interna- tional Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage, The Eurographics Association
- Language
- eng
- Publisher
- The Eurographics Association
- ISBN
- 978-3-905674-29-3
- Abstract
- As assyriologists have to handle tremendous amounts of important documents of ancient history written in cuneiform script, like the epic of Gilgamesh, we are developing an efficent system to support their daily tasks. Previous projects demonstrated the application of holography and early close-range 3D scanners for this task. Based on experiences from our previous projects in archaeology, we are focusing on processing the vast amounts of data of high resolution 3D models from todays close-range 3D scanners like the Breuckmann smartSCAN-3D-HE. The presented method exploits the high-resolution of the 3D models to extract the impressed characters as well as other features like fingerprints. Previous work typically used rendering techniques from computer graphics to visualize the characters, which then had to be processed manually. More recent approaches use methods from differential geometry for detection and extraction of coarse contour lines. These methods are computationally fast, and well-established for industrial application, but cannot cover the variations of human handwriting in form of the ? wedge shaped ? cuneiform script. To overcome the variations in size of the wedges, we choose a multiscale approach using integrating geometry. A transformation invariant function is achieved by calculating the volumes of multiple concentric spheres intersecting the volume below the 3D model's surface at each point. Due to this multiscale approach, this function is represented by the so-called feature vector. By classifying these feature vectors using auto-correlation, our system ? called GigaMesh ? can automatically extract characters, requiring only one parameter: the approximated line (wedge) width in mm. Results are shown for cuneiform tablets from the collections of the Assyriologie Heidelberg as well as from the Uruk-Warka Sammlung. Finally an outlook regarding character (en)coding and integration into related projects like the Cuneiform Digital Library Initiative (CDLI) is given.
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