Literature DB >> 23962525

Vision-based method for tracking meat cuts in slaughterhouses.

Anders Boesen Lindbo Larsen1, Marchen Sonja Hviid, Mikkel Engbo Jørgensen, Rasmus Larsen, Anders Lindbjerg Dahl.   

Abstract

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.
© 2013.

Entities:  

Keywords:  Computer vision; Image processing; Object recognition; Traceability; Tracking

Mesh:

Year:  2013        PMID: 23962525     DOI: 10.1016/j.meatsci.2013.07.023

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  1 in total

1.  Using artificial intelligence to automate meat cut identification from the semimembranosus muscle on beef boning lines.

Authors:  Satya Prakash; Donagh P Berry; Mark Roantree; Oluwadurotimi Onibonoje; Leonardo Gualano; Michael Scriney; Andrew McCarren
Journal:  J Anim Sci       Date:  2021-12-01       Impact factor: 3.159

  1 in total

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