Paper Info
Title
Towards Fish Individuality-Based Aquaculture
Abstract
By bringing concepts of precision farming to intensive aquaculture fish production, it can be optimized to be more sustainable while focusing on fish welfare criteria. This requires a shift from mass to smart production and to consider each fish as an individual. Therefore, it is required to be able to identify each fish in a tank or sea cage. In this article, we prove the feasibility of fish identification using the iris as a biometric characteristic. Based on a new dataset, captured in a controlled out of water environment: 1) a fully automated iris recognition system is presented and utilized for the experiments and 2) the distinctiveness and the stability of the iris pattern of Atlantic salmon ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Salmo salar</i> ) is assessed. Results prove the distinctiveness, which indicates that the iris pattern of Atlantic salmon is suited for biometric identification. However, the iris pattern has a low stability, which means it changes over time. Due to frequent interaction of fish and system, usually multiple times a day during feeding, there is ample opportunity to keep the biometric template up-to-date, which makes the lack of long-term stability a nonissue. It can be concluded that a biometric fish identification system is feasible, with the precondition that biometric templates of each fish are periodically updated to combat the low stability.
Year
DOI
Venue
2021
10.1109/TII.2020.3006933
IEEE Transactions on Industrial Informatics
Keywords
DocType
Volume
Fish iris identification,precision fish farming (PFF)
Journal
17
Issue
ISSN
Citations 
6
1551-3203
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Rudolf Schraml174.15
Heinz Hofbauer26715.04
Ehsaneddin Jalilian382.47
Dinara Bekkozhayeva400.68
M. M. Saberioon5174.86
Petr Císar6259.86
Andreas Uhl71958223.07