Red meat processors currently utilise manual skilled labour for their naked primal cut identification and bagging procedure. This requires significant labour from staff trained in the identification of primal cuts. The misidentification of primal cuts from operator error is also a problem faced by processors. These issues come at significant costs to red meat processors.

To overcome these issues and reduce production costs, a Naked Primal Cut Recognition Software Package has been developed. This solution was achieved by placing a 3D stereoscopic camera over the primal cut transfer conveyor to capture a high-resolution 3D image of each primal cut as it passed underneath. A neural network was developed to process the acquired 3D image to determine useful feature data and correctly identify the type of primal cut.