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Techn. Fakultät Willkommen am Institut für Informatik FAU-Logo

Daniel Stromer M. Sc.

Researcher in the Image Analysis (IMA) group at the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

3-D Reconstruction of Historical Documents

The process of aging or an already existing damage prevents the investigation of many historical writings. Commonly, the digitization process is performed by document scanning systems that photograph each page and browse through the entire book. This technique has the drawback that the documents that should be digitized have to be touched or each page has to be turned separately, which is not applicable for documents that cannot be touched, opened or unrolled anymore due to their age or pre-damages such as burns.

 

We assume that paper is made of cellulose and the writings are made with Iron Gall Ink, an ink that has been widely used since the 5th century. Not only Mozart wrote ‘The Magic Flute’ with it but also Thomas Jefferson wrote the ‘Declaration of Independence’ with that kind of ink. The ink consists of metallic ingredients allowing X-ray scanners to image its leftovers in the paper. The ink can be removed from the paper, but, however, particles are still present in deeper layers which enables the reconstruction of even erased or overwritten parts of the original writings.

 

We use state-of-the-art X-ray systems for the reconstruction of document images. Our first experiments, tested on a medical X-ray C-Arm CT robotic system, showed that the 3-D reconstruction of the ink was possible [Opens external link in new windowIVCNZ], but the imaging system was too inaccurate, such that we were only able to image a very small area of the ink. As it was not possible to set parameters to the range that we needed, we choose an X-ray system that is built for material testing [Opens external link in new windowICT].

 

To investigate the resulting output, the generated 3-D volume has to be processed such that the pages are flattened and mapped to 2-D. Therefore, a fully automatic algorithm has been developed separating and extracting the pages without the need of user interaction providing a 2-D mapped image for each page. The following Figure shows four exemplary pages that were written by our own. The page snippets have a width and height of approximately 4 cm with a letter height ranging from 2 cm to 0.25 cm. The book consists of 22 pages. The left image shows the original book, while the right images show the real page (black writings) and its automatically segmented and reconstructed CT result (bright writings). This means that we are able to read a the book's writings without the need to open it.

 

 

 

Segmentation of Fat and Fascia Layers in Ultrasound Images

The connective tissue between the fat layer and the skin termed fascia has been of interest to the clinical and zoological research to study normal skin echogenicity, thickness and hydration status, as well as the echogenicity patterns of various pathological conditions. The current state-of-the-art method for visualizing these layers is to use ultrasound imaging. By visual inspection of those (Figure below), one can see four different layers: skin, fat, fascia and muscle. Our goal is to separate the different layers fully automatically by applying appropriate segmentation algorithms. Furthermore, we want to provide a GUI for specialist such that there is no more need to manually measure the layers.