Abstract

This paper used DIDSON to get information of underwater fish and carried out the real-time multiple-target tracking, particularly the targets were dense. Analysis of fishery resources was also done through the data post-processing. Realtime data processing mainly included DIDSON image building/enhancement/filter, target detection and multiple-target tracking. Nearest neighbor clustering algorithm combined with Extended Kalman Filter was applied to the multiple-target tracking. Data post-processing mainly implemented the statistics of fish duration, swimming speed, swimming direction, trajectory length, which will provide strong technical support for the fishery resources assessment.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.