Automated screening for pathologies at abattoir through computer vision based inspection of pig carcasses

Lead Participant: Tulip Limited

Abstract

Visual inspection of carcasses is an important factor for ensuring the quality of meat products. However, manual inspection puts a strain on meat inspector resources, which effectively prevents detailed screening as, for example, for the purposes of health schemes.
The aim of this project is to develop an automated system for visual screening at abattoir. The system will analyse images taken at abattoir in order to detect a number of health hazards on pig carcasses, and to screen them at slaughter for indications of underlying subclinical diseases. The project will: (1) develop a system for capturing images of carcass; (2) acquire image data sets and have experts annotate pathologies in them; (3) develop software that learns to recognise pathologies automatically; (4) validate the system on large scale datasets for the detection of routine health hazards, and disseminate results to relevant users, incl. providing feedback to farmers.
The project brings together market leaders in meat production (Tulip) and supplier for abattoirs (Hellenic), pig levy board (BPEX), the UK’s leading centre for research into pig science (Newcastle Univ.), and experts in computer vision and pattern recognition (Newcastle Univ. and Univ. of Dundee). It will enhance confidence in detecting health hazards in pig carcasses, aiming towards automated detection of underlying subclinical disease. Feeding this back to pig farmers will increase productivity and improve efficiency on farms through preventing further diseases. Producers will be able to make decisions about improving the health of their herd through the information they receive from the abattoir. The project will thus contribute towards sustainability and competitiveness of the UK pig Industry.

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