This paper is about the reproduction of ancient texts with vectorised fonts. While for OCR only recognition rates count, a reproduction process does not necessarily require the recognition of characters. Our system aims at extracting all characters from printed historic documents without the employment of knowledge of language, font, or writing system. It searches for the best prototypes and creates a document-specific font from these glyphs. To reach this goal, many common OCR preprocessing steps are no longer adequate. We describe the necessary changes of our system that deals particularly with documents typeset in Fraktur. On the one hand, algorithms are described that extract glyphs accurately for the purpose of precise reproduction. On the other hand, classification results of extracted Fraktur glyphs are presented for different shape descriptors.

This paper discusses the importance of part-order-preservation in shape matching. A part descriptor is introduced that supports both preserving and abandoning the order of parts. The evaluation shows that retrieval results are improved by almost 38% if the original ordering is preserved.

In the GIS domain we are often faced with a great amount of shape-related data. Therefore, it is a challenging task to find concise description approaches which support the efficient retrieval of specific objects. In order to address this demand we apply a method that has recently been introduced in the context of shape-based image retrieval of two-dimensional silhouettes, namely the scope histogram. Scope histograms pertain to the group of qualitative shape descriptions as they characterise a shape by the general configuration of its parts. In particular, scope histograms allow the comparison of two shapes with constant time complexity. Despite of its low complexity, the approach achieves promising retrieval results. However, up to now the definition of scope histograms is limited to closed polygons.In this paper we investigate the application of scope histograms to the GIS domain. Since the contour of silhouettes is always closed, a restriction to closed polygons is no limitation in that domain. By contrast, it frequently is when dealing with GIS data. In this domain, we are rather often faced with open polygons; think for example of courses of rivers, borders, and coastlines. Therefore, we modify the original definition of scope histograms in order to be able to handle arbitrary polygons. Although our new definition leads to a more compact description than the original one, retrieval results are even improved by this modification.