Image Segmentation: A Survey of Methods Based on Evolutionary Computation

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@InProceedings{Liang:2014:SEAL,
  author =       "Yuyu Liang and Mengjie Zhang and Will N. Browne",
  title =        "Image Segmentation: A Survey of Methods Based on
                 Evolutionary Computation",
  booktitle =    "Proceedings 10th International Conference on Simulated
                 Evolution and Learning, SEAL 2014",
  year =         "2014",
  editor =       "Grant Dick and Will N. Browne and Peter Whigham and 
                 Mengjie Zhang and Lam Thu Bui and Hisao Ishibuchi and 
                 Yaochu Jin and Xiaodong Li and Yuhui Shi and 
                 Pramod Singh and Kay Chen Tan and Ke Tang",
  volume =       "8886",
  series =       "Lecture Notes in Computer Science",
  pages =        "847--859",
  address =      "Dunedin, New Zealand",
  month =        dec # " 15-18",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 Computer Vision, Image Segmentation, Evolutionary
                 Computation",
  isbn13 =       "978-3-319-13562-5",
  DOI =          "doi:10.1007/978-3-319-13563-2_71",
  abstract =     "Image segmentation is mainly used as a preprocessing
                 step in problems of image processing and computer
                 vision. Its performance has a great influence on
                 subsequent tasks. Evolutionary Computation (EC)
                 techniques have been introduced to the area of image
                 segmentation due to their high search capacity.
                 However, there are rarely comprehensive surveys on EC
                 based image segmentation methods, which can enable
                 researchers to get a quick understanding of this area
                 and compare the existing methods. Therefore, this paper
                 provides an overview of EC based image segmentation
                 methods, and discusses the remaining issues in this
                 area. It is observed that among all EC techniques, four
                 of them (genetic algorithms, genetic programming,
                 differential equation and partial swarm optimization)
                 are more frequently used and GAs are the most popular
                 technique. It is noted that low generalization capacity
                 and computational complexity are two common problems in
                 EC techniques applied to image segmentation.",
}

Genetic Programming entries for Yuyu Liang Mengjie Zhang Will N Browne

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