Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species
ABSTRACT: After harvesting, salmon is sorted by species, size, and quality. This is generally manually done by operators. Automation would bring repeatability, objectivity, and record‐keeping capabilities to these tasks. Machine vision (MV) and image analysis have been used in sorting many agricultu...
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crwiley:10.1111/j.1750-3841.2010.01522.x 2024-10-13T14:10:04+00:00 Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species Balaban, Murat O. Ünal Şengör, Gülgün F. Soriano, Mario Gil Ruiz, Elena Guillén 2010 http://dx.doi.org/10.1111/j.1750-3841.2010.01522.x https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1750-3841.2010.01522.x en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Journal of Food Science volume 75, issue 3 ISSN 0022-1147 1750-3841 journal-article 2010 crwiley https://doi.org/10.1111/j.1750-3841.2010.01522.x 2024-09-27T04:16:20Z ABSTRACT: After harvesting, salmon is sorted by species, size, and quality. This is generally manually done by operators. Automation would bring repeatability, objectivity, and record‐keeping capabilities to these tasks. Machine vision (MV) and image analysis have been used in sorting many agricultural products. Four salmon species were tested: pink ( Oncorhynchus gorbuscha ), red ( Oncorhynchus nerka ), silver ( Oncorhynchus kisutch ), and chum ( Oncorhynchus keta ). A total of 60 whole fish from each species were first weighed, then placed in a light box to take their picture. Weight compared with view area as well as length and width correlations were developed. In addition the effect of “hump” development (see text) of pink salmon on this correlation was investigated. It was possible to predict the weight of a salmon by view area, regardless of species, and regardless of the development of a hump for pinks. Within pink salmon there was a small but insignificant difference between predictive equations for the weight of “regular” fish and “humpy” fish. Machine vision can accurately predict the weight of whole salmon for sorting. Article in Journal/Newspaper Oncorhynchus gorbuscha Pink salmon Wiley Online Library Keta ENVELOPE(-19.455,-19.455,65.656,65.656) Journal of Food Science 75 3 |
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Open Polar |
collection |
Wiley Online Library |
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crwiley |
language |
English |
description |
ABSTRACT: After harvesting, salmon is sorted by species, size, and quality. This is generally manually done by operators. Automation would bring repeatability, objectivity, and record‐keeping capabilities to these tasks. Machine vision (MV) and image analysis have been used in sorting many agricultural products. Four salmon species were tested: pink ( Oncorhynchus gorbuscha ), red ( Oncorhynchus nerka ), silver ( Oncorhynchus kisutch ), and chum ( Oncorhynchus keta ). A total of 60 whole fish from each species were first weighed, then placed in a light box to take their picture. Weight compared with view area as well as length and width correlations were developed. In addition the effect of “hump” development (see text) of pink salmon on this correlation was investigated. It was possible to predict the weight of a salmon by view area, regardless of species, and regardless of the development of a hump for pinks. Within pink salmon there was a small but insignificant difference between predictive equations for the weight of “regular” fish and “humpy” fish. Machine vision can accurately predict the weight of whole salmon for sorting. |
format |
Article in Journal/Newspaper |
author |
Balaban, Murat O. Ünal Şengör, Gülgün F. Soriano, Mario Gil Ruiz, Elena Guillén |
spellingShingle |
Balaban, Murat O. Ünal Şengör, Gülgün F. Soriano, Mario Gil Ruiz, Elena Guillén Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species |
author_facet |
Balaban, Murat O. Ünal Şengör, Gülgün F. Soriano, Mario Gil Ruiz, Elena Guillén |
author_sort |
Balaban, Murat O. |
title |
Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species |
title_short |
Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species |
title_full |
Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species |
title_fullStr |
Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species |
title_full_unstemmed |
Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species |
title_sort |
using image analysis to predict the weight of alaskan salmon of different species |
publisher |
Wiley |
publishDate |
2010 |
url |
http://dx.doi.org/10.1111/j.1750-3841.2010.01522.x https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1750-3841.2010.01522.x |
long_lat |
ENVELOPE(-19.455,-19.455,65.656,65.656) |
geographic |
Keta |
geographic_facet |
Keta |
genre |
Oncorhynchus gorbuscha Pink salmon |
genre_facet |
Oncorhynchus gorbuscha Pink salmon |
op_source |
Journal of Food Science volume 75, issue 3 ISSN 0022-1147 1750-3841 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1111/j.1750-3841.2010.01522.x |
container_title |
Journal of Food Science |
container_volume |
75 |
container_issue |
3 |
_version_ |
1812817218814083072 |