Reconstruction for Artificial Degraded Image Using Constructive Solid Geometry and Strongly Typed Genetic Programming

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@InProceedings{Yamagiwa:2009:CISIS,
  author =       "Motoi Yamagiwa and Eiji Kikuchi and Minoru Uehara and 
                 Makoto Murakami and Masahide Yoneyama",
  title =        "Reconstruction for Artificial Degraded Image Using
                 Constructive Solid Geometry and Strongly Typed Genetic
                 Programming",
  booktitle =    "International Conference on Complex, Intelligent and
                 Software Intensive Systems, CISIS '09",
  year =         "2009",
  month =        mar,
  pages =        "162--168",
  keywords =     "genetic algorithms, genetic programming, 2-dimensional
                 sinc filter, acoustic imaging, acoustic impedance,
                 artificial degraded image reconstruction, constructive
                 solid geometry, neural network, acoustic imaging, image
                 reconstruction, neural nets",
  DOI =          "doi:10.1109/CISIS.2009.164",
  abstract =     "Acoustic imaging is effective in extreme environments
                 to take images without being influenced by optical
                 properties. However, such images tend to deteriorate
                 rapidly because acoustic impedance in air is low. It is
                 thus necessary to restore the image of the object from
                 a deteriorated image so that the object can be
                 recognized in a search. We used a neural network in the
                 previous work as a post processor and tried to
                 reconstruct the original object image. However, this
                 method needs to learn the original object image. In
                 this work, we propose combining constructive solid
                 geometry (CSG) with genetic programming (GP) as a new
                 technique that does not require learning. To confirm
                 the effectiveness of this technique, we reconstruct the
                 image of an object from a deteriorated image created by
                 applying a 2-dimensional sinc filter to the original
                 image.",
  notes =        "Also known as \cite{5066783}",
}

Genetic Programming entries for Motoi Yamagiwa Eiji Kikuchi Minoru Uehara Makoto Murakami Masahide Yoneyama

Citations