Texture Detection by Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "Mario Koeppen and Xiufen Liu",
  title =        "Texture Detection by Genetic Programming",
  booktitle =    "Proceedings of the 2001 Congress on Evolutionary
                 Computation CEC2001",
  year =         "2001",
  pages =        "867--872",
  address =      "COEX, World Trade Center, 159 Samseong-dong,
                 Gangnam-gu, Seoul, Korea",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "27-30 " # may,
  organisation = "IEEE Neural Network Council (NNC), Evolutionary
                 Programming Society (EPS), Institution of Electrical
                 Engineers (IEE)",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, texture
                 analysis, texture detection, evolutionary algorithms,
                 2D-Lookup, 2D-lookup algorithm, arbitrary image
                 processing, blind texture detection, co-occurrence
                 matrix approach, image recognition",
  ISBN =         "0-7803-6658-1",
  DOI =          "doi:10.1109/CEC.2001.934281",
  size =         "6 pages",
  abstract =     "This paper presents an approach to blind texture
                 detection in images based on adaptation of the
                 2D-lookup algorithm by genetic programming. The task of
                 blind texture detection is to separate textured regions
                 of an image from non-textured (as e.g. homogeneous)
                 ones, without any reference to a priori knowledge about
                 image content. The 2D-lookup algorithm, which
                 generalises the well-known co-occurrence matrix
                 approach of texture analysis, is based on two arbitrary
                 image processing operations. By genetic programming,
                 those image operations can be designed and adapted to a
                 given recognition goal of the whole algorithm. The idea
                 to employ such a framework for texture detection is to
                 use a random image as adaptation goal. Despite of the
                 fact that such a task has no exact solution, the system
                 is able to fulfil this task to a certain degree. This
                 degree is related to textureness in the image: the more
                 texture, the higher the degree. The paper exemplifies
                 this approach",
  notes =        "CEC-2001 - A joint meeting of the IEEE, Evolutionary
                 Programming Society, Galesia, and the IEE.

                 IEEE Catalog Number = 01TH8546C,

                 Library of Congress Number =",

Genetic Programming entries for Mario Koppen Xiufen Liu