Recognition of individual Holstein cattle by imaging body patterns

Abstract

We designed and validated a computer vision system for recognizing individual Holstein cattle by processing images of their body patterns. This system involves image capture, image pre-processing, algorithm processing, and an artificial neural network recognition algorithm. Optimum management of individuals is one of the most important factors in keeping cattle healthy and productive. In this study, an image-processing system was used to recognize individual Holstein cows by identifying body-pattern images captured by a charge-coupled device (CCD). A recognition system was developed and applied to acquire images of 49 cows. The pixel values of the body images were transformed into input data comprising binary signals for the neural network. Images of the 49 cattle were analyzed to learn input layer elements, and ten cows were used to verify the output layer elements in the neural network by using an individual recognition program. The system proved to be reliable for the individual recognition of cows in natural light.