• DocumentCode
    108859
  • Title

    Automatic Feeding Control for Dense Aquaculture Fish Tanks

  • Author

    Atoum, Yousef ; Srivastava, Steven ; Xiaoming Liu

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA
  • Volume
    22
  • Issue
    8
  • fYear
    2015
  • fDate
    Aug. 2015
  • Firstpage
    1089
  • Lastpage
    1093
  • Abstract
    This paper introduces an efficient visual signal processing system to continuously control the feeding process of fish in aquaculture tanks. The aim is to improve the production profit in fish farms by controlling the amount of feed at an optimal rate. The automatic feeding control includes two components: 1) a continuous decision on whether the fish are actively consuming feed, and 2) automatic detection of the number of excess feed populated on the water surface of the tank using a two-stage approach. The amount of feed is initially detected using the correlation filer applied to an optimum local region within the video frame, and then followed by a SVM-based refinement classifier to suppress the falsely detected feed. Having both measures allows us to accurately control the feeding process in an automated manner. Experimental results show that our system can accurately and efficiently estimate both measures.
  • Keywords
    aquaculture; image classification; particle filtering (numerical methods); support vector machines; tanks (containers); SVM-based refinement classifier; automatic feeding control; continuous decision; correlation filer; dense aquaculture fish tanks; fish farms; tank water surface; visual signal processing system; Aquaculture; Computer vision; Correlation; Feature extraction; Feeds; Monitoring; Support vector machines; Bag-of-Words (BoW); HOG; correlation filter (CF); feeding control; fish; particle filter;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2014.2385794
  • Filename
    6997987