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Computer Vision and Feeding Behavior Based Intelligent Feeding Controller for Fish in Aquaculture

Abstract : In aquaculture, the feeding technology determined the feed conversion rate and cost. However, the intelligence of existing feeding devices is not very high. they can’t change the amount of feed according to the fish appetite automatically. In order to solve the above issues, in this paper, a feeding controller based on machine vision and feeding behavior was designed on the basis of the original feeder. The hardware platform was built on the I.MX6 microcontroller, and the software was designed via the embedded Linux OS. Moreover, the feeding behavior analysis and automatic feeding control method based on image processing were also studied. Firstly, the images of fish feeding process were collected and analyzed. Then the Delaunay Triangulation was used to extract the feeding behavior parameter FIFFB (flocking index of fish feeding behavior). Finally, the feeding decision was made according to the defined threshold. Compared with the traditional feeder, the controller designed in this paper is more intelligent and can reduce feed waste. Meanwhile, water pollution also can be reduced. The automatic feeding control was realized during feeding process.
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Submitted on : Thursday, May 9, 2019 - 1:38:42 PM
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Chao Zhou, Kai Lin, Daming Xu, Chuanheng Sun, Lan Chen, et al.. Computer Vision and Feeding Behavior Based Intelligent Feeding Controller for Fish in Aquaculture. 11th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Aug 2017, Jilin, China. pp.98-107, ⟨10.1007/978-3-030-06137-1_10⟩. ⟨hal-02124258⟩



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