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Promptable sonar image segmentation for distance measurement using SAM.

Tolie, Hamidreza Farhadi; Ren, Jinchang; Hasan, Md. Junayed; Kannan, Somasundar; Fough, Nazila

Authors



Abstract

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.

Citation

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

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TOLIE 2024 Promptable sonar image (AAM) (2.4 Mb)
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/

Copyright Statement
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.




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