Research on Measuring the Bodies of Underwater Fish with Inclined Positions Using the YOLOv8 Model and a Line-Laser System

文献类型： 外文期刊

第一作者： Li, Jiakang

作者： Li, Jiakang;Zhang, Shengmao;Dai, Yang;Wu, Zuli;Li, Jiakang;Li, Penglong

作者机构：

关键词： fish farming; fish body measurement; YOLOv8; fish identification; critical point detection

期刊名称：FISHES （ 影响因子：2.1； 五年影响因子：2.4 ）

ISSN：

年卷期： 2024 年 9 卷 6 期

页码：

收录情况： SCI

摘要： Fish body measurement is essential for monitoring fish farming and evaluating growth. Non-destructive underwater measurements play a significant role in aquaculture management. This study involved annotating images of fish in aquaculture settings and utilized a line laser for underwater distance calibration and fish body inclined-angle calculation. The YOLOv8 model was employed for fish identification and key-point detection, enabling the determination of actual body dimensions through a mathematical model. The results show a root-mean-square error of 6.8 pixels for underwater distance calibration using the line laser. The pre-training YOLOv8-n, with its lower parameter counts and higher MAP values, proved more effective for fish identification and key-point detection, considering speed and accuracy. Average body length measurements within 1.5 m of the camera showed a minor deviation of 2.46% compared to manual measurements. The average relative errors for body length and width were 2.46% and 5.11%, respectively, with corresponding average absolute errors. This study introduces innovative techniques for fish body measurement in aquaculture, promoting the digitization and informatization of aquaculture processes.

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