Lehrinhalte
Automatic Image Analysis:
Visual cognition, grouping, shape descriptors, computer vision paradigm, knowledge-based image
analysis, models of the real world, formal representation of the models, modelling of uncertainty (softcomputing), invariant pattern recognition, Bayesian decision theorem, Markoff random field models,
Bayesian networks, object categorisation, automatic interpretation of maps, application to close range and
air photographs
Digital Image Processing:
Image representation in frequency domain, Fourier transform, sampling theorem, filtering, Wiener Filter,
image enhancement, edge detection, Hough transform, segmentation, interest operators, mathematical
morphology, vectorisation, texture, skeletonization, medical axis and distance transform, contour / line
tracing and -smoothing, Gestalt psychology, grouping
Hot Topics in Computer Vision Project A/ B:
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