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Real-time fish type recognition in underwater images for sustainable fishing
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

It has been investigated if it is possible to selectivly catch farmed salmon (Salmo salar L., 1758) and sea trout (Salmo trutta L., 1758) without disturbing the wild fish. A image analysis software that can separate wild from farmed salmon and salmon from sea trout has been developed. This is interesting since the advent of hydro power stations has obstructed the natural migration of these species to their natal river streams. Even though ladders have been built, fewer fish find their way back up stream. This has lead to farming of salmon and sea trout to compensate for a lower population. However, this is bad for the natural genetic variation and it would be desirable if only the wild fish could enter the rivers. The software could be installed in traps at fish ladders to help with this problem. It is common to cut the adipose fin from the farmed salmon and the lack of this fin has been used as a key character to separate farmed from wild salmon. A real-time algorithm was developed which could recognize the farmed fish with high accuracy by searching for presence or absence of the adipose fin. Additionally, two morphometric measurements were compared in order to investigate if it is possible to separate salmon from sea trout using image analysis. Preliminary tests show that it was possible to separate the species by looking at the ratio between the height of the caudal fin and the height of the caudal peduncle.

Place, publisher, year, edition, pages
2015. , 41 p.
UPTEC IT, ISSN 1401-5749 ; 14019
National Category
Engineering and Technology
URN: urn:nbn:se:uu:diva-254231OAI: oai:DiVA.org:uu-254231DiVA: diva2:817628
Available from: 2015-06-05 Created: 2015-06-05 Last updated: 2016-06-12Bibliographically approved

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