عنوان انگلیسی مقاله:
Computer vision techniques on magnetic resonance images for the non-destructive classification and quality prediction of chicken breasts affected by the White-Striping myopathy
ترجمه فارسی عنوان مقاله:
تکنیک های بینایی رایانه ای بر روی تصاویر رزونانس مغناطیسی برای طبقه بندی غیر مخرب و پیش بینی کیفیت سینه های مرغ تحت تاثیر میوپاتی White-Striping
Sciencedirect - Elsevier - Journal of Food Engineering, 306 (2021) 110633: doi:10:1016/j:jfoodeng:2021:110633
This study was designed to assess the capability of MRI-computer vision algorithms, as a non-destructive technique, to classify and predict quality characteristics of chicken breast affected by White-Striping (WS) myopathy. Samples showing moderate and severe degrees of the myopathy were analyzed together with normal samples (no WS symptoms). The influence of the computational algorithms to analyze the MRI images and the techniques of data analysis on the classification and prediction results was aimed. Computational features from both texture (GLCM) and fractal (OPFTA) algorithms were useful to i) classify WS chicken breast by means of different classification technique, Principal Component Analysis and Decision Tree, and ii) predict physico-chemical characteristics of these chicken breast with high accuracy, applying Multiple Linear Regression. The results show the feasibility of objectively classifying chicken breasts without sample destruction into two degrees of severity. This is of remarkable relevance in large processing plants where WS incidence is high and a quick decision-making is required for the fate of affected samples.
Keywords: Chicken breast | White-striping | Classification | MRI | Meat quality | Non-destructive technology