Abstract
SOLUTION is a knowledge based system, which can be used to automatically configure and adapt the low level part of image processing systems with respect to different tasks and input images. The task specification contains a characterization of the properties of the class of input images to be processed, a description of the relevant properties of the output image to be expected, requests about some general properties of the algorithms to be used, and a test image. In the configuration phase appropriate operators are selected and processing paths are assembled. In a subsequent adaptation phase the free parameters of the selected processing paths are adapted such that the specified properties of the output image are approximated as close as possible. All task specifications including the specification of the requested image properties are given in natural spoken terms like the Thickness or Parallelism of contours. The adaptation is rule based and the knowledge needed therefore can be learned automatically using a combination of different learning paradigms. This paper describes the adaptation and the learning part of SOLUTION.
The project has been supported by a grant of the Deutsche Forschungsgemeinschaft.
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© 1998 Springer-Verlag Berlin Heidelberg
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Liedtke, C.E., Münkel, H., Rost, U. (1998). SOLUTION for a learning configuration system for image processing. In: Pasqual del Pobil, A., Mira, J., Ali, M. (eds) Tasks and Methods in Applied Artificial Intelligence. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64574-8_429
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DOI: https://doi.org/10.1007/3-540-64574-8_429
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