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

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

40103 - Fishery

Project

<a href="/en/project/LM2018099" target="_blank" >LM2018099: South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses</a><br>

Continuities

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

Publication year

2022

Confidentiality

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

Name of the periodical

Applied Sciences-Basel

ISSN

2076-3417

e-ISSN

2076-3417

Volume of the periodical

12

Issue of the periodical within the volume

11

Country of publishing house

CH - SWITZERLAND

Number of pages

16

Pages from-to

nestrankovano

UT code for WoS article

000809129800001

EID of the result in the Scopus database

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