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首页> 外文期刊>IEEE transactions on industrial informatics >Towards Fish Individuality-Based Aquaculture
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Towards Fish Individuality-Based Aquaculture

机译：朝着鱼个性的水产养殖

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摘要

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 (Salmo salar) 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.
机译：通过为密集水产养殖鱼类生产带来精密耕种的概念，可以优化它可以更加可持续，同时重点关注鱼类福利标准。这需要从质量转移到智能生产，并将每条鱼视为个人。因此，需要能够识别坦克或海上笼中的每条鱼。在本文中，我们证明了使用虹膜作为生物特征的鱼识别的可行性。基于一个新的数据集，在受管制的水环境中捕获：1）呈现完全自动化的IRIS识别系统，并用于实验，2）大西洋三文鱼（沙摩酱）的虹膜模式的独特性和稳定性评估。结果证明了独特性，这表明大西洋鲑鱼的虹膜图案适用于生物识别。然而，虹膜模式具有低稳定性，这意味着它随时间变化。由于鱼类和系统的频繁相互作用，通常在喂食期间每天多次多次，有足够的机会保持生物识别模板最新，这使得缺乏长期稳定性是非的。可以得出结论，生物识别鱼识别系统是可行的，前提是每种鱼的生物识别模板都是周期性地更新的，以打击低稳定性。

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