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Robust computer vision system for marbling meat segmentation

Gabriel Fillipe Centini Campos
•
Ana Paula Ayub da Costa Barbon
•
Sylvio Barbon Junior
altro
Ana Maria Bridi
2020
  • journal article

Periodico
ELCVIA. ELECTRONIC LETTERS ON COMPUTER VISION AND IMAGE ANALYSIS
Abstract
In this study, we developed a robust automatic computer vision system for marbling meat segmentation. Our approach can segment intramuscular fat from meat samples using images acquired with different quality devices in an illumination varying environment, where there was external ambient light and artificial light; thus, professionals can apply this method without specialized knowledge in terms of image treatment or equipment, as well as without disruption to normal procedures, thereby obtaining a robust solution. The proposed approach for marbling segmentation is based on data clustering and dynamic thresholding. Experiments were performed using two datasets that comprised 82 images of 41 longissimus dorsi muscles acquired by different sampling devices. The experimental results showed that the computer vision system performed well with over 98% accuracy and a low number of false positives, regardless of the acquisition device employed.
DOI
10.5565/REV/ELCVIA.777
Archivio
https://hdl.handle.net/11368/3037254
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85086512844
https://elcvia.cvc.uab.es/article/view/v19-n1-campos
Diritti
open access
license:creative commons
license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/
FVG url
https://arts.units.it/bitstream/11368/3037254/2/777-Article Text-3375-1-10-20200317.pdf
Soggetti
  • Automation

  • Computer vision

  • Image segmentation

  • K-mean

  • Marbling meat

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