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Vessel identification based on automatic hull inscriptions recognition

The identification of ships plays a crucial role in security and managing vessel traffic for ports and onshore facilities. Existing video monitoring systems help visually identify a vessel where other systems are not present or sufficient. Readable vessel plates and hull inscriptions of detected shi...

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Autores principales: Wawrzyniak, Natalia, Hyla, Tomasz, Bodus-Olkowska, Izabela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9295957/
https://www.ncbi.nlm.nih.gov/pubmed/35853005
http://dx.doi.org/10.1371/journal.pone.0270575
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author Wawrzyniak, Natalia
Hyla, Tomasz
Bodus-Olkowska, Izabela
author_facet Wawrzyniak, Natalia
Hyla, Tomasz
Bodus-Olkowska, Izabela
author_sort Wawrzyniak, Natalia
collection PubMed
description The identification of ships plays a crucial role in security and managing vessel traffic for ports and onshore facilities. Existing video monitoring systems help visually identify a vessel where other systems are not present or sufficient. Readable vessel plates and hull inscriptions of detected ships in the video stream allow using text location and recognition methods to obtain ships’ identification names or numbers. The obtained information can be then matched with available ship registers. The automation of the process has met many challenges related to the often-low quality of available video streams, heterogeneous regulations on the marking of ships, and the specifics of natural scene text recognition, such as quickly alternating imaging conditions or the interference of the background. The main contribution of this research is a method that can identify any type of vessel in an image that has visible inscriptions (name, registration number) placed on the hull and must be registered in a public registry. The proposed method works with low-quality images with inscriptions placed under different angles and different, readable sizes. Our method recognised 91% of vessels from our test dataset. Obtained identification times have not exceeded 1s. The quality and efficiency of the proposed solution indicate that it is suitable for practical implementation in onshore monitoring systems.
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spelling pubmed-92959572022-07-20 Vessel identification based on automatic hull inscriptions recognition Wawrzyniak, Natalia Hyla, Tomasz Bodus-Olkowska, Izabela PLoS One Research Article The identification of ships plays a crucial role in security and managing vessel traffic for ports and onshore facilities. Existing video monitoring systems help visually identify a vessel where other systems are not present or sufficient. Readable vessel plates and hull inscriptions of detected ships in the video stream allow using text location and recognition methods to obtain ships’ identification names or numbers. The obtained information can be then matched with available ship registers. The automation of the process has met many challenges related to the often-low quality of available video streams, heterogeneous regulations on the marking of ships, and the specifics of natural scene text recognition, such as quickly alternating imaging conditions or the interference of the background. The main contribution of this research is a method that can identify any type of vessel in an image that has visible inscriptions (name, registration number) placed on the hull and must be registered in a public registry. The proposed method works with low-quality images with inscriptions placed under different angles and different, readable sizes. Our method recognised 91% of vessels from our test dataset. Obtained identification times have not exceeded 1s. The quality and efficiency of the proposed solution indicate that it is suitable for practical implementation in onshore monitoring systems. Public Library of Science 2022-07-19 /pmc/articles/PMC9295957/ /pubmed/35853005 http://dx.doi.org/10.1371/journal.pone.0270575 Text en © 2022 Wawrzyniak et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wawrzyniak, Natalia
Hyla, Tomasz
Bodus-Olkowska, Izabela
Vessel identification based on automatic hull inscriptions recognition
title Vessel identification based on automatic hull inscriptions recognition
title_full Vessel identification based on automatic hull inscriptions recognition
title_fullStr Vessel identification based on automatic hull inscriptions recognition
title_full_unstemmed Vessel identification based on automatic hull inscriptions recognition
title_short Vessel identification based on automatic hull inscriptions recognition
title_sort vessel identification based on automatic hull inscriptions recognition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9295957/
https://www.ncbi.nlm.nih.gov/pubmed/35853005
http://dx.doi.org/10.1371/journal.pone.0270575
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