• DocumentCode
    1593009
  • Title

    A research based on recognition algorithm of characteristics of body surface of infected fish

  • Author

    Wang, Yan ; Ye, Haijian ; Li, Baozhen

  • Author_Institution
    Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing, China
  • fYear
    2010
  • Firstpage
    155
  • Lastpage
    160
  • Abstract
    The contents of this research is how identify an infected fish through analysis of it´s image to get from the monitoring aquaculture process by computer. By studying recognition algorithms about surface images of infected fish, we identifie automatically fish diseases by computer and no need of manual intervention it. The early warning from computer makes it possible to take measures to prevent and save the loss and damages in fishing industry intensive and high-density. In accordance with fish´s own body color characteristics of a large contrast, we use Dual-threshold Difference-image Method to extract it´s contour, then can make fish´s image a structural segmentation according to the proportion of it´s head,tail and body, and further extract their color and texture feature vector in order to compare the surface feature vectors with that normal fish have ownned, we can find some infected fishes or no, and even the type of fish diseases.
  • Keywords
    aquaculture; computerised monitoring; feature extraction; fishing industry; image colour analysis; image segmentation; image texture; aquaculture process monitoring; color extraction; contour extraction; dual threshold difference image method; fishing industry; image recognition algorithm; infected fish; structural segmentation; surface image; texture feature vector; Diseases; Feature extraction; Gray-scale; Head; Image color analysis; Marine animals; Shape; Dual-threshold Difference-image Method; analysis of image; characteristics of body surface; identify an infected fish; recognition algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    World Automation Congress (WAC), 2010
  • Conference_Location
    Kobe
  • ISSN
    2154-4824
  • Print_ISBN
    978-1-4244-9673-0
  • Electronic_ISBN
    2154-4824
  • Type

    conf

  • Filename
    5665554