• DocumentCode
    2154583
  • Title

    Intelligent Video Monitor System Based on Neural Networks Analysis

  • Author

    Li, Rong ; Zhu, Li ; Yu, Sheng Sheng

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2009
  • fDate
    24-26 Sept. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Neural network analysis, an important branch in data mining, has been widely used in statistical analysis, pattern recognition, image processing, biological species division and customer division. Based on division method, the paper rationally selected initial class center, dynamically regulated the number of classification during image classification, and proposed an image recognition method. In the new method, multi-scale wavelet decomposition was firstly conducted for the image to be recognized. Then fisher transformation was performed on decomposition results of different scales which were defined as decomposition vectors. Finally, image recognition was realized in the fisher transformation domain according to the minimum absolute distance or comparative distance. The new method was proved to have high correct recognition rate and excellent recognition effect.
  • Keywords
    data mining; image classification; image recognition; neural nets; video signal processing; wavelet transforms; biological species division; customer division; data mining; fisher transformation; image classification; image processing; image recognition method; intelligent video monitor system; multiscale wavelet decomposition; neural networks analysis; pattern recognition; statistical analysis; Data mining; Image analysis; Image recognition; Intelligent networks; Intelligent systems; Monitoring; Neural networks; Pattern analysis; Pattern recognition; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3692-7
  • Electronic_ISBN
    978-1-4244-3693-4
  • Type

    conf

  • DOI
    10.1109/WICOM.2009.5304065
  • Filename
    5304065