Finding optimal transformation function for image thresholding using genetic programming

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@InProceedings{Shahbazpanahi:2014:CIMSIVP,
  author =       "S. Shahbazpanahi and S. Rahnamayan",
  booktitle =    "IEEE Symposium on Computational Intelligence for
                 Multimedia, Signal and Vision Processing (CIMSIVP
                 2014)",
  title =        "Finding optimal transformation function for image
                 thresholding using genetic programming",
  year =         "2014",
  month =        dec,
  abstract =     "In this paper, Genetic Programming (GP) is employed to
                 obtain an optimum transformation function for bi-level
                 image thresholding. The GP uses a user-prepared gold
                 sample to learn from. A magnificent feature of this
                 method is that it does not require neither a prior
                 knowledge about the modality of the image nor a large
                 training set to learn from. The performance of the
                 proposed approach has been examined on 147 X-ray lung
                 images. The transformed images are thresholded using
                 Otsu's method and the results are highly promising. It
                 performs successfully on 99percent of the tested
                 images. The proposed method can be used for other image
                 processing tasks, such as, image enhancement or
                 segmentation.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CIMSIVP.2014.7013279",
  notes =        "Also known as \cite{7013279}",
}

Genetic Programming entries for S Shahbazpanahi S Rahnamayan

Citations