Abstract
The issues of automated monitoring of the condition of mesh enclosing structures used on farms producing marine biological resources are considered. An algorithm is proposed for identifying breaks in mesh fencing underwater conditions and is implemented as a complex of programs in Python using the OpenCV computer vision library. The results of testing the algorithm are presented. It is shown that computer vision effectively copes with the classification of network cells in low-noisy and medium-noisy images. To work in more complex optical conditions, it is proposed to include a neural network module in the software package.
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Acknowledgments
The reported study was funded by RFBR, project number 19-37-90046\19 and it was supported in through computational resources provided by the Shared Services Center “Data Center of FEB RAS” (Khabarovsk).
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Smagin, A., Dubrovin, K. (2020). Applying Computer Vision Methods for Fencing Constructions Monitoring. In: Silhavy, R. (eds) Artificial Intelligence and Bioinspired Computational Methods. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1225. Springer, Cham. https://doi.org/10.1007/978-3-030-51971-1_28
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DOI: https://doi.org/10.1007/978-3-030-51971-1_28
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