YOLO fish detection with Euclidean tracking in fish farms

被引:49
作者
Wageeh, Youssef [1 ]
Mohamed, Hussam El-Din [1 ]
Fadl, Ali [1 ]
Anas, Omar [1 ]
ElMasry, Noha [1 ]
Nabil, Ayman [1 ]
Atia, Ayman [2 ,3 ]
机构
[1] Misr Int Univ, Fac Comp Sci, Cairo, Egypt
[2] Helwan Univ, Fac Comp & Artificial Intelligence, Dept Comp Sci, HCI LAB, Helwan, Egypt
[3] October Univ Modern Sci & Arts MSA, Fac Comp Sci, Cairo, Egypt
关键词
Image enhancement; Object detection; Object tracking; Fish farming;
D O I
10.1007/s12652-020-02847-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The activities of managing fish farms, like fish ponds surveillance , are one of the tough and costly fish farmers' missions. Generally, these activities are done manually, wasting time and money for fish farmers. A method is introduced in this paper which improves fish detection and fish trajectories where the water conditions is challenging. Image Enhancement algorithm is used at first to improve unclear images. Object Detection algorithm is then used on the enhanced images to detect fish. In the end, features like fish count and trajectories are extracted from the coordinates of the detected objects. Our method aims for better fish tracking and detection over fish ponds in fish farms.
引用
收藏
页码:5 / 12
页数:8
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