Prototype Mobile Vision System for Automatic Length Estimation of Olive Flounder (Paralichthys olivaceus) in Indoor Aquaculture

Real-time estimation of fish growth offers multiple benefits in indoor aquaculture, including reduced labor, lower operational costs, improved feeding efficiency, and optimized harvesting schedules. This study presents a low-cost, vision-based method for estimating the body length and weight of oliv...

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Vydáno v:Journal of marine science and engineering Ročník 13; číslo 6; s. 1167
Hlavní autoři: Kwon, Inyeong, Nguyen, Hang Thi Phuong, Prasadini Fernando, Paththige Waruni, Jeong, Hieyong, Jung, Sungju, Kim, Taeho
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.06.2025
Témata:
Accuracy
Aquaculture
Aquaculture industry
Benthos
Biomass
Body length
Body measurements
Body weight
Cameras
Coordinate transformations
Estimation
Extremities
Farmers
Fish
Fish culture
Fishes
image processing
Lagrange’s interpolating polynomial algorithm
length estimation
Length-weight relationships
length–weight relationship
Marine fishes
olive flounder
Operating costs
Paralichthys olivaceus
Pixels
Position measurement
Regression models
Swimming
Vision systems
United States
South Korea
ISSN:2077-1312, 2077-1312
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Shrnutí:Real-time estimation of fish growth offers multiple benefits in indoor aquaculture, including reduced labor, lower operational costs, improved feeding efficiency, and optimized harvesting schedules. This study presents a low-cost, vision-based method for estimating the body length and weight of olive flounder (Paralichthys olivaceus) in tank environments. A 5 × 5 cm reference grid is placed on the tank bottom, and images are captured using two fixed-position RGB smartphone cameras. Pixel measurements from the images are converted into millimeters using a calibrated pixel-to-length relationship. The system calculates fish length by detecting contour extremities and applying Lagrange interpolation. Based on the estimated length, body weight is derived using a power regression model. Accuracy was validated using both manual length measurements and Bland–Altman analysis, which indicated a mean bias of −0.007 cm and 95% limits of agreement from −0.475 to +0.462 cm, confirming consistent agreement between methods. The mean absolute error (MAE) and mean squared error (MSE) were 0.11 cm and 0.025 cm2, respectively. While optimized for benthic species such as olive flounder, this system is not suitable for free-swimming species. Overall, it provides a practical and scalable approach for non-invasive monitoring of fish growth in commercial indoor aquaculture.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2077-1312
2077-1312
DOI:10.3390/jmse13061167