Computer vision based individual fish identification using skin dot pattern

Abstract Precision fish farming is an emerging concept in aquaculture research and industry, which combines new technologies and data processing methods to enable data-based decision making in fish farming. The concept is based on the automated monitoring of fish, infrastructure, and the environment...

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Autores principales:	Petr Cisar, Dinara Bekkozhayeva, Oleksandr Movchan, Mohammadmehdi Saberioon, Rudolf Schraml
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/96ff9538a8474dfa8f767640febdf831
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spelling	oai:doaj.org-article:96ff9538a8474dfa8f767640febdf8312021-12-02T18:51:47ZComputer vision based individual fish identification using skin dot pattern10.1038/s41598-021-96476-42045-2322https://doaj.org/article/96ff9538a8474dfa8f767640febdf8312021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96476-4https://doaj.org/toc/2045-2322Abstract Precision fish farming is an emerging concept in aquaculture research and industry, which combines new technologies and data processing methods to enable data-based decision making in fish farming. The concept is based on the automated monitoring of fish, infrastructure, and the environment ideally by contactless methods. The identification of individual fish of the same species within the cultivated group is critical for individualized treatment, biomass estimation and fish state determination. A few studies have shown that fish body patterns can be used for individual identification, but no system for the automation of this exists. We introduced a methodology for fully automatic Atlantic salmon (Salmo salar) individual identification according to the dot patterns on the skin. The method was tested for 328 individuals, with identification accuracy of 100%. We also studied the long-term stability of the patterns (aging) for individual identification over a period of 6 months. The identification accuracy was 100% for 30 fish (out of water images). The methodology can be adapted to any fish species with dot skin patterns. We proved that the methodology can be used as a non-invasive substitute for invasive fish tagging. The non-invasive fish identification opens new posiblities to maintain the fish individually and not as a fish school which is impossible with current invasive fish tagging.Petr CisarDinara BekkozhayevaOleksandr MovchanMohammadmehdi SaberioonRudolf SchramlNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Petr Cisar Dinara Bekkozhayeva Oleksandr Movchan Mohammadmehdi Saberioon Rudolf Schraml Computer vision based individual fish identification using skin dot pattern
description	Abstract Precision fish farming is an emerging concept in aquaculture research and industry, which combines new technologies and data processing methods to enable data-based decision making in fish farming. The concept is based on the automated monitoring of fish, infrastructure, and the environment ideally by contactless methods. The identification of individual fish of the same species within the cultivated group is critical for individualized treatment, biomass estimation and fish state determination. A few studies have shown that fish body patterns can be used for individual identification, but no system for the automation of this exists. We introduced a methodology for fully automatic Atlantic salmon (Salmo salar) individual identification according to the dot patterns on the skin. The method was tested for 328 individuals, with identification accuracy of 100%. We also studied the long-term stability of the patterns (aging) for individual identification over a period of 6 months. The identification accuracy was 100% for 30 fish (out of water images). The methodology can be adapted to any fish species with dot skin patterns. We proved that the methodology can be used as a non-invasive substitute for invasive fish tagging. The non-invasive fish identification opens new posiblities to maintain the fish individually and not as a fish school which is impossible with current invasive fish tagging.
format	article
author	Petr Cisar Dinara Bekkozhayeva Oleksandr Movchan Mohammadmehdi Saberioon Rudolf Schraml
author_facet	Petr Cisar Dinara Bekkozhayeva Oleksandr Movchan Mohammadmehdi Saberioon Rudolf Schraml
author_sort	Petr Cisar
title	Computer vision based individual fish identification using skin dot pattern
title_short	Computer vision based individual fish identification using skin dot pattern
title_full	Computer vision based individual fish identification using skin dot pattern
title_fullStr	Computer vision based individual fish identification using skin dot pattern
title_full_unstemmed	Computer vision based individual fish identification using skin dot pattern
title_sort	computer vision based individual fish identification using skin dot pattern
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/96ff9538a8474dfa8f767640febdf831
work_keys_str_mv	AT petrcisar computervisionbasedindividualfishidentificationusingskindotpattern AT dinarabekkozhayeva computervisionbasedindividualfishidentificationusingskindotpattern AT oleksandrmovchan computervisionbasedindividualfishidentificationusingskindotpattern AT mohammadmehdisaberioon computervisionbasedindividualfishidentificationusingskindotpattern AT rudolfschraml computervisionbasedindividualfishidentificationusingskindotpattern
_version_	1718377398566649856

Computer vision based individual fish identification using skin dot pattern

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