Automated Design of Image Operators that Detect Interest Points

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@Article{Trujillo:2008:EC,
  author =       "Leonardo Trujillo and Gustavo Olague",
  title =        "Automated Design of Image Operators that Detect
                 Interest Points",
  journal =      "Evolutionary Computation",
  year =         "2008",
  volume =       "16",
  number =       "4",
  pages =        "483--507",
  month =        "Winter",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1063-6560",
  DOI =          "doi:10.1162/evco.2008.16.4.483",
  abstract =     "This work describes how evolutionary computation can
                 be used to synthesize low-level image operators that
                 detect interesting points on digital images. Interest
                 point detection is an essential part of many modern
                 computer vision systems that solve tasks such as object
                 recognition, stereo correspondence, and image indexing,
                 to name but a few. The design of the specialized
                 operators is posed as an optimization/search problem
                 that is solved with genetic programming (GP), a
                 strategy still mostly unexplored by the computer vision
                 community. The proposed approach automatically
                 synthesizes operators that are competitive with
                 state-of-the-art designs, taking into account an
                 operator's geometric stability and the global
                 separability of detected points during fitness
                 evaluation. The GP search space is defined using simple
                 primitive operations that are commonly found in point
                 detectors proposed by the vision community. The
                 experiments described in this paper extend previous
                 results (Trujillo and Olague, 2006a,b) by presenting 15
                 new operators that were synthesized through the
                 GP-based search. Some of the synthesized operators can
                 be regarded as improved man made designs because they
                 employ well-known image processing techniques and
                 achieve highly competitive performance. On the other
                 hand, since the GP search also generates what can be
                 considered as unconventional operators for point
                 detection, these results provide a new perspective to
                 feature extraction research.",
  notes =        "Part of special issue on Evolutionary Computer Vision
                 \cite{Cagnoni:2008:EC}",
}

Genetic Programming entries for Leonardo Trujillo Gustavo Olague

Citations