Image-Based Automatic Individual Identification of Fish without Obvious Patterns on the Body (Scale Pattern)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F22%3A43904489" target="_blank" >RIV/60076658:12520/22:43904489 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.3390/app12115401" target="_blank" >https://doi.org/10.3390/app12115401</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app12115401" target="_blank" >10.3390/app12115401</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Image-Based Automatic Individual Identification of Fish without Obvious Patterns on the Body (Scale Pattern)

Popis výsledku v původním jazyce

The precision fish farming concept has been widely investigated in research and is highly desirable in aquaculture as it creates opportunities for precisely controlling and monitoring fish cultivation processes and increasing fish welfare. The automatic identification of individual fish could be one of the keys to enabling individual fish treatment. In a previous study, we already demonstrated that the visible patterns on a fish&apos;s body can be used for the non-invasive individual identification of fishes from the same species (with obvious skin patterns, such as salmonids) over long-term periods. The aim of this study was to verify the possibility of using fully-automatic non-invasive photo-identification of individual fish based on natural marks on the fish&apos;s body without any obvious skin patterns. This approach is an alternative to stressful invasive tagging and marking techniques. Scale patterns on the body and operculum, as well as lateral line shapes, were used as discriminative features for the identification of individuals in a closed group of fish. We used two fish species: the European seabass Dicentrarchus labrax and the common carp Cyprinus carpio. The identification method was tested on four experimental data sets for each fish species: two separate short-term data sets (pattern variability test) and two long-term data sets (pattern stability test) for European seabass (300 individual fish) and common carp (32 individual fish). The accuracy of classification was 100% for both fish species in both the short-term and long-term experiments. According to these results, the methods used for automatic non-invasive image-based individual-fish identification can also be used for fish species without obvious skin patterns.

Název v anglickém jazyce

Image-Based Automatic Individual Identification of Fish without Obvious Patterns on the Body (Scale Pattern)

Popis výsledku anglicky

The precision fish farming concept has been widely investigated in research and is highly desirable in aquaculture as it creates opportunities for precisely controlling and monitoring fish cultivation processes and increasing fish welfare. The automatic identification of individual fish could be one of the keys to enabling individual fish treatment. In a previous study, we already demonstrated that the visible patterns on a fish&apos;s body can be used for the non-invasive individual identification of fishes from the same species (with obvious skin patterns, such as salmonids) over long-term periods. The aim of this study was to verify the possibility of using fully-automatic non-invasive photo-identification of individual fish based on natural marks on the fish&apos;s body without any obvious skin patterns. This approach is an alternative to stressful invasive tagging and marking techniques. Scale patterns on the body and operculum, as well as lateral line shapes, were used as discriminative features for the identification of individuals in a closed group of fish. We used two fish species: the European seabass Dicentrarchus labrax and the common carp Cyprinus carpio. The identification method was tested on four experimental data sets for each fish species: two separate short-term data sets (pattern variability test) and two long-term data sets (pattern stability test) for European seabass (300 individual fish) and common carp (32 individual fish). The accuracy of classification was 100% for both fish species in both the short-term and long-term experiments. According to these results, the methods used for automatic non-invasive image-based individual-fish identification can also be used for fish species without obvious skin patterns.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

40103 - Fishery

Projekt

<a href="/cs/project/LM2018099" target="_blank" >LM2018099: Jihočeské výzkumné centrum akvakultury a biodiverzity hydrocenóz</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Applied Sciences-Basel

ISSN

2076-3417

e-ISSN

2076-3417

Svazek periodika

12

Číslo periodika v rámci svazku

11

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

16

Strana od-do

nestrankovano

Kód UT WoS článku

000809129800001

EID výsledku v databázi Scopus

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