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Data for non-invasive (photo) individual fish identification of multiple species

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F23%3A43906343" target="_blank" >RIV/60076658:12520/23:43906343 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.dib.2023.109221" target="_blank" >https://doi.org/10.1016/j.dib.2023.109221</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.dib.2023.109221" target="_blank" >10.1016/j.dib.2023.109221</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Data for non-invasive (photo) individual fish identification of multiple species

  • Original language description

    This paper describes data from five studies focused on the individual fish identification of the same species. The lateral images of five fish species are present in the dataset. The dataset&apos;s primary purpose is to provide a data to develop a non-invasive and remote method of individual fish identification using fish skin patterns, which can serve as a substitute for the common invasive fish tagging. The lateral images of the whole fish body on the homogenous background for Sumatra barb, Atlantic salmon, Sea bass, Common carp and Rainbow trout are available with automatically extracted parts of the fish with skin patterns. A different number of bass - 300, Common carp - 32, Rainbow trout - 1849) were photographed by the digital camera Nikon D60 under controlled conditions. The photographs of only one side of the fish with several (from 3 to 20) repetitions were taken. Common carp, Rainbow trout and Sea bass were photographed out of the water. Atlantic salmon was photographed underwater, out of the water, and the eye of the fish was photographed by the microscope camera. Sumatra barb was photographed under the water only. For all species, except Rainbow trout, the data collection was repeated after a different period (Sumatra barb - four months, Atlantic salmon - six months, Sea bass - one month, Common carp - four months) to collect the data for a study of skin patter changes (ageing). The development of the method for photo-based individual fish identification was performed on all datasets. The identification accuracy for all species for all periods was 100% using the nearest neighbour classification. Different methods for skin pattern parametrization were used. The dataset can be used to develop remote and non-invasive individual fish identification methods. The studies focused on the discrimination power of the skin pattern can benefit from it. The changes of skin patterns due to fish ageing can be explored from the dataset. (c) 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • 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

Others

  • Publication year

    2023

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Data in Brief

  • ISSN

    2352-3409

  • e-ISSN

  • Volume of the periodical

    48

  • Issue of the periodical within the volume

    neuvedeno

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    8

  • Pages from-to

  • UT code for WoS article

    000999118500001

  • EID of the result in the Scopus database

    2-s2.0-85159292377