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In the paper, we deal with the analysis of blood and bone marrow smears. The main aim of this long term project is to obtain a relative frequency histogram of the white blood cells of different lineage and maturity. Especially for clinical application, a proper image normalization and segmentation of the colour images of blood and bone marrow smears are necessary. For the image normalization, two approaches were adopted: a) active image processing for pre acquisition standardization and b) a histogram based method for post acquisition standardization. Both methods are based on the HSI (Hue Saturation Intensity) Transform. We have developed a robust method for the declustering of the inevitable clusters of white blood cells based on a thresholded distance transform and an extended region growing algorithm that in contrast to active contours does not need any parameterization. For a successful classification, medical morphologic features are translated into feature extraction operators: the mesh structure of the cells' nucleus is analyzed using watershed transform and Gabor features, the shape of cell and nucleus is analyzed using a set of rotational invariant contour based features. The colour and granularity of the cytoplasm yield further features for classification. Current work is focused on classification using the presented features.

Conventional and new methods for the control of cyclic processes are described and compared on the basis of their performance results achieved in an aluminum extruder plant. The thrust of the work lies in the area of iterative learning control systems. After a brief description of (linear) iterative learning control, the optimizing iterative learning control of cyclic processes is presented. In this method the control input is adjusted from cycle to cycle such that a prescribed quantitative performance index is made to take on an extremum. The results which the presented methods of cyclic control yield when applied to a simulation model of an aluminum extruder are compared with one another. Finally, results obtained in an actual industrial extruder plant are given. The new method yields an increase of production by 10% as compared to methods in current use.

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