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Volume 19
Issue 6
10.3390/s19061317
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Article

A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification

by
Supu Xiu
1,
Yuanqiao Wen
2,3,*,
Haiwen Yuan
1,
Changshi Xiao
1,4,
Wenqiang Zhan
1,4,
Xiong Zou
1,4,
Chunhui Zhou
1,4 and
Sayed Chhattan Shah
5
1
School of Navigation, Wuhan University of Technology, Wuhan 430063, China
2
National Engineering Research Center for Water Transport Safety, Wuhan 430063, China
3
Intelligent Transportation Systems Research Center, Wuhan 430063, China
4
Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063, China
5
Department of Information and Communication Engineering, Hankuk University of Foreign Studies, Seoul 02450, Korea
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(6), 1317; https://doi.org/10.3390/s19061317
Received: 30 October 2018 / Revised: 10 March 2019 / Accepted: 11 March 2019 / Published: 15 March 2019
(This article belongs to the Special Issue Future Research Trends in Internet of Things and Sensor Networks)
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Abstract

In order to monitor and manage vessels in channels effectively, identification and tracking are very necessary. This work developed a maritime unmanned aerial vehicle (Mar-UAV) system equipped with a high-resolution camera and an Automatic Identification System (AIS). A multi-feature and multi-level matching algorithm using the spatiotemporal characteristics of aerial images and AIS information was proposed to detect and identify field vessels. Specifically, multi-feature information, including position, scale, heading, speed, etc., are used to match between real-time image and AIS message. Additionally, the matching algorithm is divided into two levels, point matching and trajectory matching, for the accurate identification of surface vessels. Through such a matching algorithm, the Mar-UAV system is able to automatically identify the vessel’s vision, which improves the autonomy of the UAV in maritime tasks. The multi-feature and multi-level matching algorithm has been employed for the developed Mar-UAV system, and some field experiments have been implemented in the Yangzi River. The results indicated that the proposed matching algorithm and the Mar-UAV system are very significant for achieving autonomous maritime supervision. View Full-Text
Keywords: Unmanned Aerial Vehicle (UAV); vision; Automatic Identification System (AIS); vessel identification; maritime monitoring Unmanned Aerial Vehicle (UAV); vision; Automatic Identification System (AIS); vessel identification; maritime monitoring
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MDPI and ACS Style

Xiu, S.; Wen, Y.; Yuan, H.; Xiao, C.; Zhan, W.; Zou, X.; Zhou, C.; Shah, S.C. A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification. Sensors 2019, 19, 1317. https://doi.org/10.3390/s19061317

AMA Style

Xiu S, Wen Y, Yuan H, Xiao C, Zhan W, Zou X, Zhou C, Shah SC. A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification. Sensors. 2019; 19(6):1317. https://doi.org/10.3390/s19061317

Chicago/Turabian Style

Xiu, Supu, Yuanqiao Wen, Haiwen Yuan, Changshi Xiao, Wenqiang Zhan, Xiong Zou, Chunhui Zhou, and Sayed C. Shah. 2019. "A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification" Sensors 19, no. 6: 1317. https://doi.org/10.3390/s19061317

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