• DocumentCode
    3303607
  • Title

    Extension Theory for Classification of the Stored-Grain Insects

  • Author

    Zhang, Hongtao ; Hu, Yuxia

  • Author_Institution
    Sch. of Electr. Power, North China Univ. of Water Conservancy & Electr. Power, Zhengzhou, China
  • fYear
    2010
  • fDate
    24-25 April 2010
  • Firstpage
    758
  • Lastpage
    760
  • Abstract
    The design of the classifier is one of the important parts of the online detection system of the stored-grain insects based on the image recognition technology. The classification of the insects was of many image feature parameters, and the mixing degree among feature parameters of various species of the insects was large. The extension theory was proposed to be applied to the automatic classification of the insects. A method that constructed the matter element matrix of the insects was put forward based on the mean and variance of the image features. After calculating the correlation degrees between the insect to be recognized and the nine species of insects, the insect could be recognized by the maximum integrated correlation degree criterion. The experiment confirms that the recognition of the insects based on the extension theory is practical and feasible by the training and analyzing of the samples of the insects.
  • Keywords
    Artificial neural networks; Image recognition; Insects; Machine vision; Man machine systems; Pollution; Set theory; Stability; Water conservation; Water storage; classification; extension theory; matter-element matrix; stored-grain insects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
  • Conference_Location
    Kaifeng, China
  • Print_ISBN
    978-1-4244-6595-8
  • Electronic_ISBN
    978-1-4244-6596-5
  • Type

    conf

  • DOI
    10.1109/MVHI.2010.40
  • Filename
    5532478