Semantic feature extraction using genetic programming in image retrieval

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Li:2004:ICPR,
  author =       "Qingyong Li and Hong Hu and Zhongzhi Shi",
  title =        "Semantic feature extraction using genetic programming
                 in image retrieval",
  booktitle =    "Proceedings of the 17th International Conference on
                 Pattern Recognition, ICPR 2004",
  year =         "2004",
  volume =       "1",
  pages =        "648--651",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming, content-based
                 retrieval, feature extraction, image retrieval, image
                 texture, visual perception Tamura texture model,
                 content based image retrieval, human visual perception,
                 linguistic expression, semantic feature extraction,
                 texture extraction, visual feature extraction",
  DOI =          "doi:10.1109/ICPR.2004.1334248",
  size =         "4 pages",
  abstract =     "One of the big hurdles facing current content-based
                 image retrieval (CBIR) is the semantic gap between the
                 low-level visual features and the high-level semantic
                 features. We proposed an approach to describe and
                 extract the global texture semantic features. According
                 to the Tamura texture model, we use the linguistic
                 variable to describe the texture semantics, so it
                 becomes possible to depict the image in linguistic
                 expression such as coarse, fine. We use genetic
                 programming to simulate the human visual perception and
                 extract the semantic features value. Our experiments
                 show that the semantic features have good accordance
                 with the human perception, and also have good retrieval
                 performance. In some extent, our approach bridges the
                 semantic gap in CBIR.",
  notes =        "also known as \cite{1334248}",
}

Genetic Programming entries for Qingyong Li Hong Hu Zhongzhi Shi

Citations