Wide-area ship target recognition method based on motion and appearance features

YAN Ronghui; XIE Haicheng; HUA Minheng; YANG Jianfeng

doi:10.19693/j.issn.1673-3185.02320

Volume 17 Issue 1

Mar. 2022

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Article Navigation > Chinese Journal of Ship Research > 2022 > 17(1): 227-234

YAN R H, XIE H C, HUA M H, et al. Wide-area ship target recognition method based on motion and appearance features[J]. Chinese Journal of Ship Research, 2022, 17(1): 227–234 doi: 10.19693/j.issn.1673-3185.02320

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Wide-area ship target recognition method based on motion and appearance features

doi: 10.19693/j.issn.1673-3185.02320

1.
Wenzheng College, Soochow University, Suzhou 215104, China
2.
School of Electronic and Information Engineering, Soochow University, Suzhou 215006, China

Received Date: 2021-03-18
Rev Recd Date: 2021-06-20

Available Online: 2022-02-22

Publish Date: 2022-03-02

Abstract

This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective The aim of this paper is to proposes methods for better recognizing and positioning ships sailing in critical and wide-area waterways during monitoring operation. Methods Based on video surveillance technology, the joint use of the motion and appearance features of ship target is carried out to realize a wide-area multi-dimensional recognition function via the combination of background subtraction based moving object detection algorithm and deep learning based target recognition algorithm. In addition, the improved approaches including water ripple noise reduction, hierarchical moving object detection and window segmentation of waterway monitoring image are put forward to further improve recognition accuracy. Results The field demonstration results show that the improved methods proposed in this paper allow the accurate recognition of a ship of any type or size on the monitoring screen, and the use of conventional cameras can also achieve the recognition and position of a ship navigating a water area within a radius of 3 km. Conclusions The improved methods proposed in this study have a range of advantages including wide-area monitoring, complete coverage of ship types and sizes, automatic target recognition and robust anti-interference ability.
- wide-area waterway monitoring,
- ship recognition,
- motion detection,
- multi-dimensional features,
- YOLO detection algorithm

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References

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