Abstract
The main purpose of the conducted research is the development and experimental verification of the methods for detection of fish feeding as well as checking its uniformity in the recirculating aquaculture systems (RAS) using machine vision. A particular emphasis has been set on the methods useful for rainbow trout farming.
Obtained results, based on the analysis of individual video frames, convince that the estimation of feeding uniformity in individual RAS-based farming ponds is possible using the selected local image features without the necessity of camera calibration. The experimental results have been achieved for the images acquired in the RAS-based rainbow trout farming ponds and verified using some publicly available video sequences from tilapia and catfish feeding.
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Acknowledgments
The research was conducted within the project no 00002-6521.1-OR1600001/17/20 financed by the “Fisheries and the Sea” program.
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Lech, P., Okarma, K., Korzelecka-Orkisz, A., Tański, A., Formicki, K. (2021). Monitoring the Uniformity of Fish Feeding Based on Image Feature Analysis. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12745. Springer, Cham. https://doi.org/10.1007/978-3-030-77970-2_6
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