HAMIDREZA FARHADI TOLIE h.farhadi-tolie@rgu.ac.uk
Research Student
HAMIDREZA FARHADI TOLIE h.farhadi-tolie@rgu.ac.uk
Research Student
Professor Jinchang Ren j.ren@rgu.ac.uk
Professor of Computing Science
Dr Md Junayed Hasan j.hasan@rgu.ac.uk
Research Fellow A
Dr Somasundar Kannan s.kannan1@rgu.ac.uk
Lecturer
Dr Nazila Fough n.fough1@rgu.ac.uk
Lecturer
The subsea environment presents numerous challenges for robotic vision, including non-uniform light attenuation, backscattering, floating particles, and low-light conditions, which significantly degrade underwater images. This degradation impacts robotic operations that heavily rely on environmental feedback. However, these limitations can be mitigated using sonar imaging, which employs sound pulses instead of light. In this paper, we explore the use of small, affordable sonar devices for automatic target object localization and distance measurement. Specifically, we propose using a promptable image segmentation method to identify target objects within sonar images, leveraging its ability to identify connected components without requiring labeled datasets. Through laboratory experiments, we analyzed the usability of the Ping360 single-beam sonar and verified the effectiveness of our approach in the automatic identification and distance measurement of objects made from various materials. The collected raw and processed data alongside the source code of the proposed approach will be shared at https://2ithub.com/hfarhaditolieIPSIS-ADM.
TOLIE, H.F., REN, J., HASAN, M.J., KANNAN, S. and FOUGH, N. 2024. Promptable sonar image segmentation for distance measurement using SAM. In Proceedings of the 2024 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea; learning to measure sea health parameters (IEEE MetroSea 2024), 14-16 October 2024, Portorose, Slovenia. Piscataway: IEEE [online], pages 229-233. Available from: https://doi.org/10.1109/metrosea62823.2024.10765703
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 2024 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea; learning to measure sea health parameters (IEEE MetroSea 2024) |
Start Date | Oct 14, 2024 |
End Date | Oct 16, 2024 |
Acceptance Date | Jul 13, 2024 |
Online Publication Date | Oct 14, 2024 |
Publication Date | Dec 31, 2024 |
Deposit Date | Dec 6, 2024 |
Publicly Available Date | Dec 20, 2024 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Peer Reviewed | Peer Reviewed |
Pages | 229-233 |
ISBN | 9798350379006 |
DOI | https://doi.org/10.1109/metrosea62823.2024.10765703 |
Keywords | Sonar image segmentation; Distance measurement; Ping360; Single-beam sonar |
Public URL | https://rgu-repository.worktribe.com/output/2613780 |
External URL | https://2ithub.com/hfarhaditolieIPSIS-ADM |
TOLIE 2024 Promptable sonar image (AAM)
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