Abstract
Quality assurance of drinking water is vital in the current world. This research used fish to monitor and forewarn water quality in real time. This research adopted a Gaussian mixture model (GMM) to conduct background modeling, extract moving foregrounds, and automatically judge, screen, and dispose of various contours in the binary images through image preprocessing and morphological processing, and outlined the changing curves of indicators using a computer. The experimental results demonstrated that the above method was successful. This system was able to monitor the active state of a fish in real-time and accurately raise the alarm in the case of an abnormal condition. Based on this research, it would be easy to measure other indicators and develop extended functions that would be beneficial for follow up studies.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (No: 61571377, 61471308), and the Science & Technology Development Projects from the Transportation Administration of Fujian Province (No: 201437).
Ethical approval. All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.
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Lin, CR., Chen, Y., Lin, XZ., Yuan, F., Zhu, Y. (2016). Water Monitoring System Based on Recognition of Fish Behavior. In: Hussain, A. (eds) Electronics, Communications and Networks V. Lecture Notes in Electrical Engineering, vol 382. Springer, Singapore. https://doi.org/10.1007/978-981-10-0740-8_47
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DOI: https://doi.org/10.1007/978-981-10-0740-8_47
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