Robust computer vision system for marbling meat segmentation
Campos, Gabriel Fillipe Centini (Universidade Estadual de Londrina. Department of Computer Science)
Seixas Jr., José Luis (Eötvös Loránd Tudományegyetem. Department of Data Science and Engineering)
Barbon, Ana Paula A. C. (Universidade Estadual de Londrina. Department of Zootechnology)
Felinto, Alan Salvany (Universidade Estadual de Londrina. Department of Computer Science)
Bridi, Ana Maria (Universidade Estadual de Londrina. Department of Zootechnology)
Barbon Jr., Sylvio (Universidade Estadual de Londrina. Department of Computer Science)

Data:	2020
Resum:	In this study, we developed a robust automatic computer vision system for marbling meat segmentation. Our approach can segment muscle fat in various marbled meat samples using images acquired with different quality devices in an uncontrolled environment, where there was external ambient light and artificial light; thus, professionals can apply this method without specialized knowledge in terms of sample treatments 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.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Automation ; Computer vision ; Image segmentation ; K-means ; Marbling meat ; Image analysis and processing ; Applications ; Food engineering
Publicat a:	ELCVIA, Vol. 19 Núm. 1 (2020) , p. 15-27 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v19-n1-campos
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/370831
Adreça original: https://elcvia.cvc.uab.cat/article/view/v19-n1-campos
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/10.5565-rev-elcvia.777
DOI: 10.5565/rev/elcvia.777

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