Martin Stommel

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—Document enhancement tools are a valuable help in the study of historic documents. Given proper filter settings, many effects that impair the legibility can be evened out (e.g. washed out ink, stained and yellowed paper). However, because of differing authors, languages, handwritings, fonts and paper conditions, no single filter parameter set fits all(More)
This paper describes a method to recognize and classify complex objects in digital images. To this end, a uniform representation of prototypes is introduced. The notion of a prototype describes a set of local features which allow to recognize objects by their appearance. During a training step a genetic algorithm is applied to the prototypes to optimize(More)
In this paper we present and evaluate a simple but effective machine learning algorithm that we call Bitvector Machine: Feature vectors are partitioned along component-wise quantiles and converted into bitvectors that are learned. It is shown that the method is efficient in both training and classification. The effectiveness of the method is analysed(More)
In many computer vision problems, the essential information can be most easily interpreted in the form of structural models. However, the computation of distances between structural models can be difficult, since small changes in the underlying image data often cause significant differences in the graph layout. The other way around, changes in the link(More)