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A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification
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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470540/ https://www.ncbi.nlm.nih.gov/pubmed/30884771 http://dx.doi.org/10.3390/s19061317 |
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author | Xiu, Supu Wen, Yuanqiao Yuan, Haiwen Xiao, Changshi Zhan, Wenqiang Zou, Xiong Zhou, Chunhui Shah, Sayed Chhattan |
author_facet | Xiu, Supu Wen, Yuanqiao Yuan, Haiwen Xiao, Changshi Zhan, Wenqiang Zou, Xiong Zhou, Chunhui Shah, Sayed Chhattan |
author_sort | Xiu, Supu |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6470540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64705402019-04-26 A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification Xiu, Supu Wen, Yuanqiao Yuan, Haiwen Xiao, Changshi Zhan, Wenqiang Zou, Xiong Zhou, Chunhui Shah, Sayed Chhattan Sensors (Basel) Article 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. MDPI 2019-03-15 /pmc/articles/PMC6470540/ /pubmed/30884771 http://dx.doi.org/10.3390/s19061317 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xiu, Supu Wen, Yuanqiao Yuan, Haiwen Xiao, Changshi Zhan, Wenqiang Zou, Xiong Zhou, Chunhui Shah, Sayed Chhattan A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification |
title | A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification |
title_full | A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification |
title_fullStr | A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification |
title_full_unstemmed | A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification |
title_short | A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification |
title_sort | multi-feature and multi-level matching algorithm using aerial image and ais for vessel identification |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470540/ https://www.ncbi.nlm.nih.gov/pubmed/30884771 http://dx.doi.org/10.3390/s19061317 |
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