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Automatic ship monitoring method in bridge area by fusion of vision and AIS
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Zijun DU1, 2, Yixiong HE1, 2, Deqing YU1, 2, Xingya ZHAO1, 2, Rui ZHANG1, 2, Liwen HUANG1, 2
Navigation of China | 2025, 48(1) : 34 - 42
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Navigation of China | 2025, 48(1): 34-42
• Marine Traffic Safety •
Automatic ship monitoring method in bridge area by fusion of vision and AIS
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Zijun DU1, 2, Yixiong HE1, 2, Deqing YU1, 2, Xingya ZHAO1, 2, Rui ZHANG1, 2, Liwen HUANG1, 2
Affiliations
  • 1.School of Navigation, Wuhan University of Technology, Wuhan 430063, China
  • 2.Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, China
Published: 2025-03-25 doi: 10.3969/j.issn.1000-4653.2025.01.005
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To ensure the safety of navigation in the bridge area, this paper proposes a ship automatic monitoring method based on the fusion of vision and AIS (Automatic Identification System). The ship contour information in the image is extracted by the YOLOv5 (You Only Look Once version 5) target detection algorithm and the Canny algorithm. A distance, azimuth, and height measurement model of the visual target in the bridge area is constructed to achieve the three-dimensional positioning of the ship. An abnormal behavior detection model is established using the ship navigation situation data from the fusion of vision and AIS to automatically identify and monitor monitoring of dangerous ships in the bridge area. The experimental results show that: In cases of single and multiple ships, the accuracy of visual and AIS data association is 98.45% and 91.29%, respectively; The method can effectively monitor the motion state of ships in the bridge area. This paper provides an effective method for ensuring the safety of ships and bridges.

ship automatic monitoring method  /  target detection  /  data fusion  /  abnormal behavior detection
Zijun DU, Yixiong HE, Deqing YU, Xingya ZHAO, Rui ZHANG, Liwen HUANG. Automatic ship monitoring method in bridge area by fusion of vision and AIS[J]. Navigation of China, 2025 , 48 (1) : 34 -42 . DOI: 10.3969/j.issn.1000-4653.2025.01.005
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Year 2025 volume 48 Issue 1
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Article Info
doi: 10.3969/j.issn.1000-4653.2025.01.005
  • Receive Date：2023-11-08
  • Online Date：2026-03-17
  • Published：2025-03-25
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  • Received：2023-11-08
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Affiliations
    1.School of Navigation, Wuhan University of Technology, Wuhan 430063, China
    2.Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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