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




 

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

Courtesy: MDPI
Received: 30 October 2018 / Revised: 10 March 2019 / Accepted: 11 March 2019 / Published: 15 March 2019

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.

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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

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