Publicado en Spanish Journal of Agriculture Research (SJAR) Accurate individual animal identification provides the producers with useful information to take management decisions about an individual animal or about the complete herd. This identification task is also important to ensure the integrity of the food chain. Consequently, many consumers are turning their attention to issues of quality in animal food production methods. This work describes an implemented solution for individual beef identification, taking in the time from cattle shipment arrival at the slaughterhouse until the animals are slaughtered and cut up. Our beef identification approach is image-based and the pursued goals are the correct automatic extraction and matching between some numeric information extracted from the beef ear-tag and the corresponding one from the Bovine Identification Document (BID). The achieved correct identification results by our method are near 90%, by considering the practica
GAVAB es un grupo multidisciplinar formado por profesores de la Universidad Rey Juan Carlos que recoge diferentes líneas de investigación encuadradas en el área de conocimiento de las Ciencias de la Computación y de la Inteligencia Artificial.