Identification of writers of handwritten historical documents is an important and challenging task. In this paper we present several feature extraction and classification approaches for the identification of writers in historical Arabic manuscripts. The approaches are able to successfully identify writers of multipage documents. The feature extraction methods rely on different principles, such as contour-, textural-and key point-based and the classification schemes are based on averaging and voting. For all experiments a dedicated data set based on a publicly available database is used. The experiments show promising results and the best performance was achieved using a novel feature extraction based on key point descriptors.
Laser brazing of zinc coated steel is a widely established manufacturing process in the automotive sector, where high quality requirements must be fulfilled. The strength, impermeablitiy and surface appearance of the joint are particularly important for judging its quality. The development of an on-line quality control system is highly desired by the industry. This paper presents recent works on the development of such a system, which consists of two cameras operating in different spectral ranges. For the evaluation of the system, seam imperfections are created artificially during experiments. Finally image processing algorithms for monitoring process parameters based the captured images are presented
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