Abstract Fingerling counting in fish farming is still a problem to be solved, although there are some technological solutions used in experimental cases and controlled environments. In this paper, a fingerlings counter is evaluated using a new image database with 448 videos of the Pintado Real® fingerlings species. A total of 21,402 combinations of 6 parameters of the fingerlings counter were tested. In the training phase, 314 videos were randomly selected, which represent 70% of the database. The remaining 30%, corresponding to 134 videos, were used for testing. Focusing on the parameters that best recognize and track the fingerlings of Pintado Real®, it was obtained Pearson Coefficient of 0.9803 and a quadratic average error of 2.65 when comparing the manual and automatic counting. The results obtained six parameters sets that achieved these metrics, reaching higher performance on the fingerlings counter from a new image database. The image database used in our research is available for researchers.

中文翻译：

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用于评估自动鱼种计数的新图像数据集

摘要 鱼类养殖中的鱼种计数仍然是一个有待解决的问题，尽管在实验案例和受控环境中使用了一些技术解决方案。在本文中，使用包含 Pintado Real® 鱼种物种的 448 个视频的新图像数据库评估鱼种计数器。总共测试了鱼种计数器 6 个参数的 21,402 个组合。在训练阶段，随机选择了 314 个视频，占数据库的 70%。剩余的 30%，对应 134 个视频，用于测试。关注最能识别和跟踪 Pintado Real® 鱼种的参数，在比较手动和自动计数时，获得了 0.9803 的皮尔逊系数和 2.65 的二次平均误差。结果获得了实现这些指标的六个参数集，在来自新图像数据库的鱼种计数器上达到了更高的性能。我们研究中使用的图像数据库可供研究人员使用。