The use of computer vision techniques as noninvasive tools to monitor parameters related to the well-being and productive performance of cattle and pigs

Among a wide range of factors that can affect animals’ wellbeing, stress levels and health status have been identified as relevant factors in production animals. The increasing awareness about animal welfare and the impact that it has on farm productivity has been promoting scientific research and the development of novel and less invasive methods to monitor animals and obtain measurements that can be used as indicators to assess animal wellbeing, including stress and health status. Research presented in this thesis deals with red-green-blue (RGB) and thermal infrared (TIR) imagery, and computer vision techniques, as non-invasive tools to measure physiological changes in cattle and pigs to assist in the assessment of their stress and health. One study was conducted to evaluate the performance of the proposed methods, which were used to analyse RGB and TIR imagery to measure eye-temperature, heart rate (HR) and respiration rate (RR) in cattle. The study was performed in a robotic dairy farm, where TIR and RGB cameras recorded ten dairy cows during six handling procedures, across two consecutive days. Simultaneously, core body temperature, HR and RR were measured using standard methods for comparison with the data obtained from the recorded images using the developed algorithms. A feature tracking algorithm was developed to facilitate the processing of RGB videos, which showed an accuracy between 92% and 95% depending on the area analysed. From the physiological parameters analysed, the highest correlations were observed between eye-temperature and intravaginal temperature (r = 0.8; P<0.01), and between remote RR and the RR obtained from visual observations (r = 0.87; P<0.01). A further two studies were carried out to implement the proposed computer-based methods to remotely measure eye-temperature, heart rate and respiration rate of cattle, and to investigate whether these measures could be used to evaluate the physiological response of cattle to stressful situations