Vision-based method for tracking meat cuts in slaughterhouses

•We demonstrate a vision-based method to perform tracking of pork loins.•We are able to recognize 211 pork loins between two photo sessions.•Selected loins have undergone rough treatment to simulate slaughterhouse handling.•Our method is a competitive alternative to current more intrusive tracking systems.

Meat traceability is important for linking process and quality parameters from the individual meat cuts back to the production data from the farmer that produced the animal. Current tracking systems rely on physical tagging, which is too intrusive for individual meat cuts in a slaughterhouse environment. In this article, we demonstrate a computer vision system for recognizing meat cuts at different points along a slaughterhouse production line. More specifically, we show that 211 pig loins can be identified correctly between two photo sessions. The pig loins undergo various perturbation scenarios (hanging, rough treatment and incorrect trimming) and our method is able to handle these perturbations gracefully. This study shows that the suggested vision-based approach to tracking is a promising alternative to the more intrusive methods currently available.