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Vision-based method for tracking meat cuts in slaughterhouses.

Anders Boesen Lindbo Larsen¹, Marchen Sonja Hviid, Mikkel Engbo Jørgensen

¹Technical University of Denmark, Lyngby, Denmark.

|August 22, 2013

Summary

This summary is machine-generated.

A new computer vision system accurately identifies pig loins in a slaughterhouse, offering a non-intrusive alternative to physical tags. This meat traceability method handles production line challenges effectively.

Keywords:

Computer vision Image processing Object recognition Traceability Tracking

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Area of Science:

Agricultural Science
Computer Vision
Food Science

Background:

Meat traceability is crucial for linking production data to meat quality.
Current physical tagging methods are too intrusive for individual meat cuts in slaughterhouses.

Purpose of the Study:

To demonstrate a computer vision system for recognizing meat cuts on a production line.
To provide a non-intrusive alternative for meat traceability.

Main Methods:

A computer vision system was developed to identify pig loins.
The system was tested on 211 pig loins across two photo sessions.
Perturbation scenarios including hanging, rough handling, and trimming were simulated.

Main Results:

The computer vision system achieved correct identification of pig loins between photo sessions.
The system demonstrated robustness in handling various perturbation scenarios encountered in a slaughterhouse.

Conclusions:

The vision-based approach is a promising, non-intrusive method for meat traceability.
This technology can enhance the link between farm production data and meat quality parameters.