Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform

Jiaxing Wang, Mingqiang Yang, Zhongjun Ding, Qinghe Zheng, Deqiang Wang, Kidiyo Kpalma, Jinchang Ren

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Abstract

Variations in the quantity of plankton impact the entire marine ecosystem. It is of great significance to accurately assess the dynamic evolution of the plankton for monitoring the marine environment and global climate change. In this paper, a novel method is introduced for deep-sea plankton community detection in marine ecosystem using an underwater robotic platform. The videos were sampled at a distance of 1.5 m from the ocean floor, with a focal length of 1.5–2.5 m. The optical flow field is used to detect plankton community. We showed that for each of the moving plankton that do not overlap in space in two consecutive video frames, the time gradient of the spatial position of the plankton are opposite to each other in two consecutive optical flow fields. Further, the lateral and vertical gradients have the same value and orientation in two consecutive optical flow fields. Accordingly, moving plankton can be accurately detected under the complex dynamic background in the deep-sea environment. Experimental comparison with manual ground-truth fully validated the efficacy of the proposed methodology, which outperforms six state-of-the-art approaches.
Original languageEnglish
Article number6720
Number of pages18
JournalSensors
Volume21
Issue number20
DOIs
Publication statusPublished - 10 Oct 2021

Keywords

  • image motion analysis
  • image processing
  • optical flow
  • underwater robotic

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