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Updated: Oct 23, 2025

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Computer vision based individual fish identification using skin dot pattern.

Petr Cisar1, Dinara Bekkozhayeva2, Oleksandr Movchan2

  • 1Laboratory of Signal and Image Processing, Institute of Complex Systems, FFPW, CENAKVA, University of South Bohemia in Ceske Budejovice, Zámek 136, Nové Hrady, 373 33, Czech Republic. cisar@frov.jcu.cz.

Scientific Reports
|August 20, 2021
PubMed
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Precision fish farming uses automated identification of individual fish by their unique skin patterns. This 100% accurate, non-invasive method enables personalized fish care and biomass estimation in aquaculture.

Area of Science:

  • Aquaculture
  • Animal Identification
  • Biotechnology

Background:

  • Precision fish farming requires individual fish identification for optimized management.
  • Current methods like invasive tagging are suboptimal for large-scale aquaculture.
  • Automated, non-invasive identification systems are needed.

Purpose of the Study:

  • To develop a fully automatic methodology for individual Atlantic salmon identification using skin dot patterns.
  • To assess the accuracy and long-term stability of this identification method.
  • To demonstrate the potential for non-invasive fish tagging in aquaculture.

Main Methods:

  • Developed a methodology for automatic identification of Atlantic salmon based on skin dot patterns.
  • Tested the method on 328 individual fish.

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Last Updated: Oct 23, 2025

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  • Evaluated pattern stability over six months using out-of-water images.

    • Main Results:

    • Achieved 100% identification accuracy for 328 Atlantic salmon.
    • Maintained 100% identification accuracy over six months for aging studies.
    • Demonstrated the methodology's adaptability to other fish species with similar patterns.

    Conclusions:

    • The developed methodology provides a fully automatic and highly accurate non-invasive method for individual fish identification.
    • This technology can replace invasive tagging, enabling individualized fish management and improving aquaculture practices.
    • The system offers new possibilities for monitoring fish health, biomass, and implementing tailored treatments.