Irregularity Detection in Net Pens Exploiting Computer Vision
Peer reviewed, Journal article
Submitted version
Date
2022Metadata
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Abstract
Protecting the remaining wild salmon stock in Norway is of utmost importance and requires that farmed salmon cannot escape from aquaculture sites. As holes in net-cages are responsible for a large fraction of the escaped salmon the industry has to perform frequent inspections of the _sh cage integrity. In this paper we propose an image processing and computer vision based attention mechanism towards a more automated _sh-cage inspection. The presented algorithm allows to indicate areas in videos showing net-pen locations where potential holes are present. We show the e_ectivity of the approach on video-recordings of holes also in commercial _sh-cages.