Cristin-resultat-ID: 2076241
Sist endret: 11. januar 2023, 15:30
NVI-rapporteringsår: 2022
Resultat
Vitenskapelig artikkel
2022

Irregularity Detection in Net Pens Exploiting Computer Vision

Bidragsytere:
  • Christian Schellewald og
  • Annette Stahl

Tidsskrift

IFAC-PapersOnLine
ISSN 2405-8963
e-ISSN 2405-8963
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2022
Volum: 55
Hefte: 31
Sider: 415 - 420

Beskrivelse Beskrivelse

Tittel

Irregularity Detection in Net Pens Exploiting Computer Vision

Sammendrag

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 fish cage integrity.In this paper we propose an image processing and computer vision based attention mechanism towards a more automated fish-cage inspection. The presented algorithm allows to indicate areas in videos showing net-pen locations where potential holes are present. We show the effectivity of the approach on video-recordings of holes also in commercial fish-cages.

Bidragsytere

Christian Schellewald

  • Tilknyttet:
    Forfatter
    ved Havbruk ved SINTEF Ocean

Annette Stahl

  • Tilknyttet:
    Forfatter
    ved Institutt for teknisk kybernetikk ved Norges teknisk-naturvitenskapelige universitet
1 - 2 av 2