Behavior recognition method for individual laying hen based on computer vision

Animal behavior is an important animal welfare evaluation index. In order to achieve the automatic monitoring of laying hens behavior, a method of an individual laying hen behavior recognition based on computer vision technology was proposed in this study. The behaviors of moving, drinking, feeding, preening, shaking, resting, wing flapping, exploration and wing lifting of individual laying hen in single image could be distinguished by tracing the displacement and location of the laying hen, and the track activities and movement trajectories in a long time could be tracked using Bayesian classification with ten parameters calculated from the hen images using image processing techniques. The correlation coefficient of distance from laying hen images upper and lower contour to least-squares fitting ellipse longitudinal could effectively track the hens head, and the recognition rate of grooming behavior and exploratory behavior were improved. The test results of 9219 images indicated that the recognition rates of moving, drinking, feeding, preening, shaking, resting, wing flapping, exploration and wing lifting were 99.4%, 80.7%, 87.3%, 81.6%, 69.8%, 86.2%, 100%, 54.0% and 64.6%, respectively.