Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform
Wang, Jiaxing and Yang, Mingqiang and Ding, Zhongjun and Zheng, Qinghe and Wang, Deqiang and Kpalma, Kidiyo and Ren, Jinchang (2021) Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform. Sensors, 21 (20). 6720. ISSN 1424-8220 (https://doi.org/10.3390/s21206720)
Preview |
Text.
Filename: Wang_etal_Sensors_2021_Detection_of_the_deep_sea_plankton_community_in_marine_ecosystem_with_underwater_robotic_platform.pdf
Final Published Version License: Download (2MB)| Preview |
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.
ORCID iDs
Wang, Jiaxing, Yang, Mingqiang, Ding, Zhongjun, Zheng, Qinghe, Wang, Deqiang, Kpalma, Kidiyo and Ren, Jinchang ORCID: https://orcid.org/0000-0001-6116-3194;-
-
Item type: Article ID code: 78108 Dates: DateEvent10 October 2021Published5 October 2021AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering
Technology > Hydraulic engineering. Ocean engineeringDepartment: Technology and Innovation Centre > Sensors and Asset Management
Faculty of Engineering > Electronic and Electrical EngineeringDepositing user: Pure Administrator Date deposited: 11 Oct 2021 09:23 Last modified: 11 Nov 2024 13:16 URI: https://strathprints.strath.ac.uk/id/eprint/78108