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
作者： Li, Jiakang 1 ; Zhang, Shengmao 1 ; Li, Penglong 3 ; Dai, Yang 1 ; Wu, Zuli 1 ;
作者机构： 1.Chinese Acad Fishery Sci, Minist Agr & Rural Affairs, East China Sea Fisheries Res Inst, Key Lab Fisheries Remote Sensing, Shanghai 200090, Peoples R China
2.Shanghai Ocean Univ, Coll Informat Technol, Shanghai 200090, Peoples R China
3.Dalian Ocean Univ, Sch Nav & Naval Architecture, Dalian 116023, Peoples R China
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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