Non-invasive identification of individuals of Atlantic salmon (tent data) ...
Non-invasive identification of individuals of Atlantic salmon (tent data). 328 fish were sampled. 30 fish were tagged for next data collection. totally 4 data collection were done. The fish were photographed in tent out of water. The fish were photographed on the green background for simple fish loc...
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2023
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Online Access: | https://dx.doi.org/10.5281/zenodo.7690930 https://zenodo.org/record/7690930 |
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ftdatacite:10.5281/zenodo.7690930 2023-06-11T04:10:16+02:00 Non-invasive identification of individuals of Atlantic salmon (tent data) ... Bartunek, Dinara Cisar, Petr 2023 https://dx.doi.org/10.5281/zenodo.7690930 https://zenodo.org/record/7690930 unknown Zenodo https://dx.doi.org/10.5281/zenodo.7690929 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess non-invasive identification individual identification photo-identification Dataset dataset 2023 ftdatacite https://doi.org/10.5281/zenodo.769093010.5281/zenodo.7690929 2023-06-01T12:02:42Z Non-invasive identification of individuals of Atlantic salmon (tent data). 328 fish were sampled. 30 fish were tagged for next data collection. totally 4 data collection were done. The fish were photographed in tent out of water. The fish were photographed on the green background for simple fish localization. Each image was processed separately. First the green background was detected based on the defined value of the green in HSV color space. The backgound was used as the area of fish appearance. In the secodn step the fish was segmented on the background using the specific color of the fish in HSV color space. The fish was detected as the largest object. Some morphological operations were used to correct fish shape. The object was rotated to the horizontal position. The fish tail was removed by the algorithm because it was detected on some images and not detected on the rest. Therefore the algorithm detects the begining of back tail as the most narrow place at back part of the fish. The lenght of the fish ... Dataset Atlantic salmon DataCite Metadata Store (German National Library of Science and Technology) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
non-invasive identification individual identification photo-identification |
spellingShingle |
non-invasive identification individual identification photo-identification Bartunek, Dinara Cisar, Petr Non-invasive identification of individuals of Atlantic salmon (tent data) ... |
topic_facet |
non-invasive identification individual identification photo-identification |
description |
Non-invasive identification of individuals of Atlantic salmon (tent data). 328 fish were sampled. 30 fish were tagged for next data collection. totally 4 data collection were done. The fish were photographed in tent out of water. The fish were photographed on the green background for simple fish localization. Each image was processed separately. First the green background was detected based on the defined value of the green in HSV color space. The backgound was used as the area of fish appearance. In the secodn step the fish was segmented on the background using the specific color of the fish in HSV color space. The fish was detected as the largest object. Some morphological operations were used to correct fish shape. The object was rotated to the horizontal position. The fish tail was removed by the algorithm because it was detected on some images and not detected on the rest. Therefore the algorithm detects the begining of back tail as the most narrow place at back part of the fish. The lenght of the fish ... |
format |
Dataset |
author |
Bartunek, Dinara Cisar, Petr |
author_facet |
Bartunek, Dinara Cisar, Petr |
author_sort |
Bartunek, Dinara |
title |
Non-invasive identification of individuals of Atlantic salmon (tent data) ... |
title_short |
Non-invasive identification of individuals of Atlantic salmon (tent data) ... |
title_full |
Non-invasive identification of individuals of Atlantic salmon (tent data) ... |
title_fullStr |
Non-invasive identification of individuals of Atlantic salmon (tent data) ... |
title_full_unstemmed |
Non-invasive identification of individuals of Atlantic salmon (tent data) ... |
title_sort |
non-invasive identification of individuals of atlantic salmon (tent data) ... |
publisher |
Zenodo |
publishDate |
2023 |
url |
https://dx.doi.org/10.5281/zenodo.7690930 https://zenodo.org/record/7690930 |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_relation |
https://dx.doi.org/10.5281/zenodo.7690929 |
op_rights |
Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5281/zenodo.769093010.5281/zenodo.7690929 |
_version_ |
1768384586925998080 |