Estimation of fat cover of bovine carcases by means of computer vision system (CVS)
The aims of this study were to obtain percentages of meat and fat cover for SEUROP classification system reference images using a computer vision system (CVS) and to calculate classification intervals which could be used in the future for construction of cheap and easy to use classification devices for small slaughterhouses. Lowest percentages of fat cover were found for the first class marked as “low” (the lowest fat content) and they gradually increased to the last class marked as “very high” (the highest fat content). Based on the obtained results, decision making intervals were proposed. In the present study, classification only refers to classification of adult bovine animals based on fat cover.