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Towards optimal fillet portioning: a computer vision system for determining the fish fillet volume

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 15 No. 1 (2025)

DOI
10.11591/ijece.v15i1.pp550-558
ISSN
2722-2578, 2088-8708
Published
2025-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Portioning large fish fillets for packaging is usually performed manually by skilled workers. Automating this process and obtaining packaged products with attractive shapes and affordable weights will be beneficial for promoting purchase decisions. Towards developing an automated fish fillet portioning system, this study investigated a computer vision approach for determining the fillet volume. A belt conveyor would transport a fish fillet to the image capture booth, where its cross-section areas would be calculated for volume determination. The developed system could be operated with a conveyor speed ranging from 7.5 to 30.6 mm/s. The system performance was evaluated at a conveyor speed of 7.5 mm/s using small catfish fillets from 142.2 to 225.4 cm3. A mean percent error of 9.2% was observed, and the smallest percent error of 3.8% was obtained with a 225.4 cm3 fillet. With minor measurement errors obtained for larger fillets, the proposed computer vision system showed great potential for developing a cost-effective automated system for customized fish fillet partitioning to accelerate purchase decisions and also for quality control and classification of the fish fillets.

Collaboration network of the authors

13 authors · 34 co-authorship links · 4 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Can Tho University
  • Kien Giang University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Van-Linh LamKien Giang University2
Phúc Hậu LêCan Tho University2
Huy-Thanh HoCan Tho University2
Khanh NguyenCan Tho University1
Vy-Khang TranCan Tho University1
Hai X. PhamCan Tho University1
Van-Muot NguyenCan Tho University1
Hoang-Dung NguyenCan Tho University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Towards optimal fillet portioning: a computer vision system for determining the fish fillet volume</dc:title><dc:creator>Nguyen, Chanh-Nghiem</dc:creator><dc:creator>Vo, Ngọc-Tan</dc:creator><dc:creator>Nguyen, Ngoc-Thanh</dc:creator><dc:creator>Tran, Nhut-Thanh</dc:creator><dc:creator>Nguyen, Chi-Ngon</dc:creator><dc:description>&lt;jats:p&gt;Portioning large fish fillets for packaging is usually performed manually by skilled workers. Automating this process and obtaining packaged products with attractive shapes and affordable weights will be beneficial for promoting purchase decisions. Towards developing an automated fish fillet portioning system, this study investigated a computer vision approach for determining the fillet volume. A belt conveyor would transport a fish fillet to the image capture booth, where its cross-section areas would be calculated for volume determination. The developed system could be operated with a conveyor speed ranging from 7.5 to 30.6 mm/s. The system performance was evaluated at a conveyor speed of 7.5 mm/s using small catfish fillets from 142.2 to 225.4 cm3. A mean percent error of 9.2% was observed, and the smallest percent error of 3.8% was obtained with a 225.4 cm3 fillet. With minor measurement errors obtained for larger fillets, the proposed computer vision system showed great potential for developing a cost-effective automated system for customized fish fillet partitioning to accelerate purchase decisions and also for quality control and classification of the fish fillets.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2025-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v15i1.pp550-558</dc:identifier><dc:identifier>10.11591/ijece.v15i1.pp550-558</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 15 No 1 (2025); 550</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/36055/17963</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>