Automated Sorting System for Skeletal Deformities in Cultured Fishes

Anomaly occurrence is a constant worldwide problem in aquaculture and it raises economic and animal welfare issues. The early-stage removal of abnormal fish from the stocks is necessary, and the sorting process remains manual worldwide, causing a significant increase in personnel cost and delays in the production cycle. The purpose of this project is to develop an integrated automated system for the valid sorting of farmed fishes by removing these with shape or colour anomalies or skeletal deformities. The sorting will be based on vision analysis and shape pattern recognition techniques

Development of A Non-Invasive System for the Automatic Detection of Cattle Lameness

Lameness is a crucial welfare issue in the modern dairy cattle industry, that if not identified and treated early causes losses in milk production and leads to early culling of animals. At present, the most common methods used for lameness detection and assessment are various visual locomotion scoring systems, which are labour-intensive, and the results may be subjective. The purpose of this project is to develop an integrated system for early detection of lameness in cattle, using force plate gait analysis and pattern recognition techniques to identify changes in gait which indicate the onset of lameness. The system will be tested on the natural onset of lameness in an organised farm environment