YOLO fish detection with Euclidean tracking in fish farms

被引:0
作者
Youssef Wageeh
Hussam El-Din Mohamed
Ali Fadl
Omar Anas
Noha ElMasry
Ayman Nabil
Ayman Atia
机构
[1] Misr International University,Faculty of Computer Science
[2] Helwan University,HCI
[3] October University for Modern Sciences and Arts (MSA),LAB, Department of Computer Science, Faculty of Computers and Artificial Intelligence
来源
Journal of Ambient Intelligence and Humanized Computing | 2021年 / 12卷
关键词
Image enhancement; Object detection; Object tracking; Fish farming;
D O I
暂无
中图分类号
学科分类号
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:7
相关论文
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