• DocumentCode
    158144
  • Title

    Automated Video Imaging System for Counting Deep-Sea Bioluminescence Organisms Events

  • Author

    Mazzei, Luca ; Marini, Simone ; Craig, Jessica ; Aguzzi, Jacopo ; Fanelli, Emanuela ; Priede, Imants G.

  • Author_Institution
    ISMAR (Marine Sci. Inst.), Lerici, Italy
  • fYear
    2014
  • fDate
    24-24 Aug. 2014
  • Firstpage
    57
  • Lastpage
    64
  • Abstract
    Bioluminescence refers to the production of ecologically functional light by living organisms. It is widespread in the marine environment, where it occurs in a broad range of phyla. The deep pelagic ocean is the largest biome on earth and is chronically under-sampled. Underwater camera systems offer a rapid sampling method for this zone. In the current study, the ICDeep (Image Intensied Charge Coupled Device for Deep-sea research) profiler was used to record digital video of bioluminescent organisms through the deep water column. This work proposes a new automatic detection and counting methods for bioluminescent organisms represented as ashes within video data acquired through the camera based on computer vision algorithms. The proposed method has been validated by a ground truthed sequence of bioluminescent events resulting in a high correct detection rate and real time processing execution.
  • Keywords
    CCD image sensors; bioluminescence; cameras; computer vision; geophysical image processing; object recognition; sampling methods; video signal processing; ICDeep; automated video imaging system; automatic counting methods; computer vision algorithms; deep pelagic ocean; deep-sea bioluminescence organism event counting; digital video; ecologically functional light production; image intensified charge coupled device for deep-sea research; living organisms; marine environment; phyla; rapid sampling method; real time processing execution; underwater camera systems; Ash; Bioluminescence; Biomedical imaging; Bismuth; Cameras; Computer vision; Organisms; bioluminescent organisms; deep sea; under- water computer vision; underwater object recognition.; video tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision for Analysis of Underwater Imagery (CVAUI), 2014 ICPR Workshop on
  • Conference_Location
    Stockholm
  • Print_ISBN
    978-1-4799-6709-4
  • Type

    conf

  • DOI
    10.1109/CVAUI.2014.15
  • Filename
    6961269