Prediction of the weight of Alaskan Pollock using image analysis
Determining the size and quality attributes of fish by machine vision is gaining acceptance and increasing use in the seafood industry. Objectivity, speed, and record keeping are advantages in using this method. The objective of this work was to develop the mathematical correlations to predict the w...
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ftkuetahyadumlup:oai:openaccess.dpu.edu.tr:20.500.12438/5543 2023-07-30T04:04:41+02:00 Prediction of the weight of Alaskan Pollock using image analysis Balaban M.O. Chombeau M. Cirban D. Gümüş B. 2010 https://hdl.handle.net/20.500.12438/5543 https://doi.org/10.1111/j.1750-3841.2010.01813.x eng eng 10.1111/j.1750-3841.2010.01813.x Journal of Food Science Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı 0022-1147 https://dx.doi.org/10.1111/j.1750-3841.2010.01813.x https://hdl.handle.net/20.500.12438/5543 75 8 E552 E556 info:eu-repo/semantics/closedAccess Image processing View area Weight Zlaskan pollock article 2010 ftkuetahyadumlup https://doi.org/20.500.12438/554310.1111/j.1750-3841.2010.01813.x 2023-07-12T15:59:28Z Determining the size and quality attributes of fish by machine vision is gaining acceptance and increasing use in the seafood industry. Objectivity, speed, and record keeping are advantages in using this method. The objective of this work was to develop the mathematical correlations to predict the weight of whole Alaskan Pollock (Theragra chalcogramma) based on its view area from a camera. One hundred and sixty whole Pollock were obtained fresh, within 2 d after catch from a Kodiak, Alaska, processing plant. The fish were first weighed, then placed in a light box equipped with a Nikon D200 digital camera. A reference square of known surface area was placed by the fish. The obtained image was analyzed to calculate the view area of each fish. The following equations were used to fit the view area (X) compared with weight (Y) data: linear, power, and 2nd-order polynomial. The power fit (Y = A·XB) gave the highest R2 for the fit (0.99). The effect of fins and tail on the accuracy of the weight prediction using view area were evaluated. Removing fins and tails did not improve prediction accuracy. Machine vision can accurately predict the weight of whole Pollock. © 2010 Institute of Food Technologists®. Article in Journal/Newspaper Kodiak Theragra chalcogramma Alaska Kütahya Dumlupınar University Institutional Repository Journal of Food Science 75 8 E552 E556 |
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Kütahya Dumlupınar University Institutional Repository |
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language |
English |
topic |
Image processing View area Weight Zlaskan pollock |
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Image processing View area Weight Zlaskan pollock Balaban M.O. Chombeau M. Cirban D. Gümüş B. Prediction of the weight of Alaskan Pollock using image analysis |
topic_facet |
Image processing View area Weight Zlaskan pollock |
description |
Determining the size and quality attributes of fish by machine vision is gaining acceptance and increasing use in the seafood industry. Objectivity, speed, and record keeping are advantages in using this method. The objective of this work was to develop the mathematical correlations to predict the weight of whole Alaskan Pollock (Theragra chalcogramma) based on its view area from a camera. One hundred and sixty whole Pollock were obtained fresh, within 2 d after catch from a Kodiak, Alaska, processing plant. The fish were first weighed, then placed in a light box equipped with a Nikon D200 digital camera. A reference square of known surface area was placed by the fish. The obtained image was analyzed to calculate the view area of each fish. The following equations were used to fit the view area (X) compared with weight (Y) data: linear, power, and 2nd-order polynomial. The power fit (Y = A·XB) gave the highest R2 for the fit (0.99). The effect of fins and tail on the accuracy of the weight prediction using view area were evaluated. Removing fins and tails did not improve prediction accuracy. Machine vision can accurately predict the weight of whole Pollock. © 2010 Institute of Food Technologists®. |
format |
Article in Journal/Newspaper |
author |
Balaban M.O. Chombeau M. Cirban D. Gümüş B. |
author_facet |
Balaban M.O. Chombeau M. Cirban D. Gümüş B. |
author_sort |
Balaban M.O. |
title |
Prediction of the weight of Alaskan Pollock using image analysis |
title_short |
Prediction of the weight of Alaskan Pollock using image analysis |
title_full |
Prediction of the weight of Alaskan Pollock using image analysis |
title_fullStr |
Prediction of the weight of Alaskan Pollock using image analysis |
title_full_unstemmed |
Prediction of the weight of Alaskan Pollock using image analysis |
title_sort |
prediction of the weight of alaskan pollock using image analysis |
publishDate |
2010 |
url |
https://hdl.handle.net/20.500.12438/5543 https://doi.org/10.1111/j.1750-3841.2010.01813.x |
genre |
Kodiak Theragra chalcogramma Alaska |
genre_facet |
Kodiak Theragra chalcogramma Alaska |
op_relation |
10.1111/j.1750-3841.2010.01813.x Journal of Food Science Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı 0022-1147 https://dx.doi.org/10.1111/j.1750-3841.2010.01813.x https://hdl.handle.net/20.500.12438/5543 75 8 E552 E556 |
op_rights |
info:eu-repo/semantics/closedAccess |
op_doi |
https://doi.org/20.500.12438/554310.1111/j.1750-3841.2010.01813.x |
container_title |
Journal of Food Science |
container_volume |
75 |
container_issue |
8 |
container_start_page |
E552 |
op_container_end_page |
E556 |
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1772816250640007168 |