Skip to main content

Research Repository

Advanced Search

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

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

Authors

Jiaxing Wang

Mingqiang Yang

Zhongjun Ding

Qinghe Zheng

Deqiang Wang

Kidiyo Kpalma

Jinchang Ren



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.

Citation

WANG, J., YANG, M., DING, Z., ZHENG, Q., WANG, D., KPALMA, K. and REN, J. 2021. Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform. Sensors [online], 21(20), article 6720. Available from: https://doi.org/10.3390/s21206720

Journal Article Type Article
Acceptance Date Oct 5, 2021
Online Publication Date Oct 10, 2021
Publication Date Oct 31, 2021
Deposit Date May 6, 2022
Publicly Available Date Jun 6, 2022
Journal Sensors
Print ISSN 1424-8220
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 21
Issue 20
Pages 6720
DOI https://doi.org/10.3390/s21206720
Keywords Image motion analysis; Image processing; Optical flow; Underwater robotic
Public URL https://rgu-repository.worktribe.com/output/1580666

Files





You might also like



Downloadable Citations