Conception, Implementation and Validation of an Algorithm for the automated Chaining and simultaneously Parameter Optimization of Image Processing Operations
Abstract:
One method to detect faults in surfaces is the application of image processing operations, in order to emphasize areas with faults. Usually, a suitable chaining of image processing operations has to be found. During the search, suitable image processing operations are manually sequenced. This has to be repeated till the following goals are reached: Areas with faults should be emphasized and areas without faults should be suppressed. Even in the case of comparable few image processing operations, with each having one or more parameters, this is a tedious task. With increasing number of operations there is a high increase in the effort, which is known as 'combinatorial explosion ' of choices. This paper describes a framework for evolutionary algorithms and a concrete realization, which performs this task automatically. It is designed to use a priori knowledge of the user to narrow the possible search space. Also there are given some results by working with this algorithm.
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