Improving the Canny edge detector using automatic programming: Improving the filter

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@InProceedings{Magnusson:2016:ICIVC,
  author =       "Lars Vidar Magnusson and Roland Olsson",
  booktitle =    "2016 International Conference on Image, Vision and
                 Computing (ICIVC)",
  title =        "Improving the Canny edge detector using automatic
                 programming: Improving the filter",
  year =         "2016",
  pages =        "36--40",
  abstract =     "We have used automatic programming, a machine learning
                 technique related to inductive logic programming and
                 genetic programming, to make the Canny edge detector
                 better at identifying contours in natural images. We
                 present an improved version of the filter used in the
                 first stage of the Canny algorithm. We show that the
                 mean performance of the Canny algorithm with the
                 improved filter on a popular test set of natural images
                 has been improved by 1.4percent. Our result shows that
                 the heuristic design provides a statistically
                 significant increase in performance-without adding
                 extra processing steps or adding additional
                 information. This suggests that the filter should be
                 used as a standard part of image analysis platforms.
                 The inferred heuristic filter exhibits an ability to
                 retain detail without sacrificing noise reduction. This
                 is further evidence that automatic programming is well
                 suited for generating heuristics for image analysis
                 problems.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICIVC.2016.7571270",
  month =        aug,
  notes =        "Also known as \cite{7571270}",
}

Genetic Programming entries for Lars Vidar Magnusson J Roland Olsson

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