• DocumentCode
    2110477
  • Title

    The fresh classification of pork detection based on multi-data fusion

  • Author

    Guo Peiyuan ; Bi Song ; Chen Tianhua ; Xu Guannan ; Liu Xing

  • Author_Institution
    Coll. of Comput. & Inf. Eng., Beijing Technol. & Bus. Univ., Beijing, China
  • fYear
    2010
  • fDate
    29-31 July 2010
  • Firstpage
    2735
  • Lastpage
    2738
  • Abstract
    In order to find a quick valid scientific way to identify meat freshness, the article analyses the measuring mechanism of identifying to fresh degree of meat, and designs one set of intellectual detection and identification system that is based on electronic information technology, photoelectric detection technique, image processing technology and neural network model recognition technology. In order to achieve the freshness of the pork inspection classification identification, neural network technology micro-parameters of non-coherent multi-data fusion detection methods was Researched.
  • Keywords
    biology computing; biomedical optical imaging; food products; image classification; inspection; neural nets; object detection; photoelectricity; production engineering computing; sensor fusion; electronic information technology; identification system; image processing technology; intellectual detection system; meat fresh classification; neural network model recognition technology; noncoherent multidata fusion detection methods; photoelectric detection technique; pork detection; pork inspection classification identification; Artificial neural networks; Image color analysis; Microorganisms; Proteins; Software; Standards; Transforms; Identifying Meat Freshness; Neural Network; Pattern-Recognition; Photo-electricity Measuring; Plaque Area;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2010 29th Chinese
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-6263-6
  • Type

    conf

  • Filename
    5573541