Image Processing for Ice Floe Analyses in Broken-ice Model Testing

The ice floe shape and size distribution are important ice parameters in ice-structure analyses. Before performing an analysis at full scale, the dynamic positioning (DP) experiments in model ice at the Hamburg Ship Model Basin (HSVA) allow for the testing of relevant image processing algorithms. A...

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Published in:Cold Regions Science and Technology
Main Authors: Zhang, Qin, Skjetne, Roger, Metrikin, Ivan, Løset, Sveinung
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2015
Subjects:
Online Access:http://hdl.handle.net/11250/2384299
https://doi.org/10.1016/j.coldregions.2014.12.004
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spelling ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2384299 2023-05-15T15:06:12+02:00 Image Processing for Ice Floe Analyses in Broken-ice Model Testing Zhang, Qin Skjetne, Roger Metrikin, Ivan Løset, Sveinung 2015-01-02T17:53:39Z http://hdl.handle.net/11250/2384299 https://doi.org/10.1016/j.coldregions.2014.12.004 eng eng Elsevier http://www.sciencedirect.com/science/article/pii/S0165232X14002201 Cold Regions Science and Technology 2015, 111:27-38 urn:issn:0165-232X http://hdl.handle.net/11250/2384299 https://doi.org/10.1016/j.coldregions.2014.12.004 cristin:1189396 111 Cold Regions Science and Technology VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581 VDP::Technology: 500::Marine technology: 580::Offshore technology: 581 Arktisk teknologi / Arctic Technology Isforvaltning / Ice Management Miljøovervåkning / Environmental monitoring Journal article Peer reviewed 2015 ftntnutrondheimi https://doi.org/10.1016/j.coldregions.2014.12.004 2019-09-17T06:50:34Z The ice floe shape and size distribution are important ice parameters in ice-structure analyses. Before performing an analysis at full scale, the dynamic positioning (DP) experiments in model ice at the Hamburg Ship Model Basin (HSVA) allow for the testing of relevant image processing algorithms. A complete overview image of the ice floe distribution in the ice tank was generated from the experiments. An image processing method based on a gradient vector flow (GVF) snake and a distance transform is proposed to identify individual ice floes. Ice floe characteristics such as position, area, and size distribution are obtained. A model of the managed ice field's configuration, including identification of overlapping floes, is also proposed for further studies in ice-force numerical simulations. Finally, the proposed algorithm is applied to an ice surveillance video to further illustrate its applicability to ice management. © 2014 Elsevier B.V. All rights reserved. This is the authors' accepted and refereed manuscript to the article. Locked until 2016-12-15. Article in Journal/Newspaper Arctic Arktis* NTNU Open Archive (Norwegian University of Science and Technology) Arctic Cold Regions Science and Technology 111 27 38
institution Open Polar
collection NTNU Open Archive (Norwegian University of Science and Technology)
op_collection_id ftntnutrondheimi
language English
topic VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581
VDP::Technology: 500::Marine technology: 580::Offshore technology: 581
Arktisk teknologi / Arctic Technology
Isforvaltning / Ice Management
Miljøovervåkning / Environmental monitoring
spellingShingle VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581
VDP::Technology: 500::Marine technology: 580::Offshore technology: 581
Arktisk teknologi / Arctic Technology
Isforvaltning / Ice Management
Miljøovervåkning / Environmental monitoring
Zhang, Qin
Skjetne, Roger
Metrikin, Ivan
Løset, Sveinung
Image Processing for Ice Floe Analyses in Broken-ice Model Testing
topic_facet VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581
VDP::Technology: 500::Marine technology: 580::Offshore technology: 581
Arktisk teknologi / Arctic Technology
Isforvaltning / Ice Management
Miljøovervåkning / Environmental monitoring
description The ice floe shape and size distribution are important ice parameters in ice-structure analyses. Before performing an analysis at full scale, the dynamic positioning (DP) experiments in model ice at the Hamburg Ship Model Basin (HSVA) allow for the testing of relevant image processing algorithms. A complete overview image of the ice floe distribution in the ice tank was generated from the experiments. An image processing method based on a gradient vector flow (GVF) snake and a distance transform is proposed to identify individual ice floes. Ice floe characteristics such as position, area, and size distribution are obtained. A model of the managed ice field's configuration, including identification of overlapping floes, is also proposed for further studies in ice-force numerical simulations. Finally, the proposed algorithm is applied to an ice surveillance video to further illustrate its applicability to ice management. © 2014 Elsevier B.V. All rights reserved. This is the authors' accepted and refereed manuscript to the article. Locked until 2016-12-15.
format Article in Journal/Newspaper
author Zhang, Qin
Skjetne, Roger
Metrikin, Ivan
Løset, Sveinung
author_facet Zhang, Qin
Skjetne, Roger
Metrikin, Ivan
Løset, Sveinung
author_sort Zhang, Qin
title Image Processing for Ice Floe Analyses in Broken-ice Model Testing
title_short Image Processing for Ice Floe Analyses in Broken-ice Model Testing
title_full Image Processing for Ice Floe Analyses in Broken-ice Model Testing
title_fullStr Image Processing for Ice Floe Analyses in Broken-ice Model Testing
title_full_unstemmed Image Processing for Ice Floe Analyses in Broken-ice Model Testing
title_sort image processing for ice floe analyses in broken-ice model testing
publisher Elsevier
publishDate 2015
url http://hdl.handle.net/11250/2384299
https://doi.org/10.1016/j.coldregions.2014.12.004
geographic Arctic
geographic_facet Arctic
genre Arctic
Arktis*
genre_facet Arctic
Arktis*
op_source 111
Cold Regions Science and Technology
op_relation http://www.sciencedirect.com/science/article/pii/S0165232X14002201
Cold Regions Science and Technology 2015, 111:27-38
urn:issn:0165-232X
http://hdl.handle.net/11250/2384299
https://doi.org/10.1016/j.coldregions.2014.12.004
cristin:1189396
op_doi https://doi.org/10.1016/j.coldregions.2014.12.004
container_title Cold Regions Science and Technology
container_volume 111
container_start_page 27
op_container_end_page 38
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