Using machine vision for investigation of changes in pig group lying patterns

Pig lying patterns can provide information on environmental factors affecting production efficiency, health and welfare. The aim of this study was to investigate the feasibility of using image processing and the Delaunay triangulation method to detect change in group lying behaviour of pigs under commercial farm conditions and relate this to changing environmental temperature. Two pens of 22 growing pigs were monitored during 15 days using top view CCD cameras. Animals were extracted from their background using image processing algorithms, and the x-y coordinates of each binary image were used for ellipse fitting algorithms to localize each pig. By means of the region properties and perimeter of each Delaunay Triangulation, it was possible with high accuracy to automatically find the changes in lying posture and location within the pen of grouped pigs caused by temperature changes.