A Genetic Programming Approach for Classification of Textures Based on Wavelet Analysis

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@InProceedings{Chen:2007:WISP,
  author =       "Zheng Chen and Siwei Lu",
  title =        "A Genetic Programming Approach for Classification of
                 Textures Based on Wavelet Analysis",
  booktitle =    "IEEE International Symposium on Intelligent Signal
                 Processing, WISP 2007",
  year =         "2007",
  month =        oct,
  pages =        "1--6",
  keywords =     "genetic algorithms, genetic programming, feature
                 extraction, texture classification, wavelet analysis,
                 wavelet decomposition, feature extraction, image
                 classification, image texture, wavelet transforms",
  DOI =          "doi:10.1109/WISP.2007.4447575",
  abstract =     "In this paper, we propose a method for classifying
                 textures using Genetic Programming (GP). Texture
                 features are extracted from the energy of subimages of
                 the wavelet decomposition. The GP is then used to
                 evolve rules, which are arithmetic combinations of
                 energy features, to identify whether a texture image
                 belongs to certain class. Instead of using only one
                 rule to discriminate the samples, a set of rules are
                 used to perform the prediction by applying the majority
                 voting technique. In our experiment results based on
                 Brodatz dataset, the proposed method has achieved
                 99.6percent test accuracy on an average. In addition,
                 the experiment results also show that classification
                 rules generated by this approach are robust to some
                 noises on textures.",
  notes =        "Also known as \cite{4447575}",
}

Genetic Programming entries for Zheng Chen Siwei Lu

Citations