Real-time fish type recognition in underwater images for sustainable fishing

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 intere...

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Main Author: Jonsson, Fritjof
Format: Others
Language:English
Published: Uppsala universitet, Institutionen för informationsteknologi 2015
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-254231
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spelling ndltd-UPSALLA1-oai-DiVA.org-uu-2542312016-06-13T05:11:32ZReal-time fish type recognition in underwater images for sustainable fishingengJonsson, FritjofUppsala universitet, Institutionen för informationsteknologi2015It 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. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-254231UPTEC IT, 1401-5749 ; 14019application/pdfinfo:eu-repo/semantics/openAccess
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language English
format Others
sources NDLTD
description 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.
author Jonsson, Fritjof
spellingShingle Jonsson, Fritjof
Real-time fish type recognition in underwater images for sustainable fishing
author_facet Jonsson, Fritjof
author_sort Jonsson, Fritjof
title Real-time fish type recognition in underwater images for sustainable fishing
title_short Real-time fish type recognition in underwater images for sustainable fishing
title_full Real-time fish type recognition in underwater images for sustainable fishing
title_fullStr Real-time fish type recognition in underwater images for sustainable fishing
title_full_unstemmed Real-time fish type recognition in underwater images for sustainable fishing
title_sort real-time fish type recognition in underwater images for sustainable fishing
publisher Uppsala universitet, Institutionen för informationsteknologi
publishDate 2015
url http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-254231
work_keys_str_mv AT jonssonfritjof realtimefishtyperecognitioninunderwaterimagesforsustainablefishing
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