1 February 1991 Image analysis for estimating the weight of live animals
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Proceedings Volume 1379, Optics in Agriculture; (1991) https://doi.org/10.1117/12.25092
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
Many components of animal production have been automated. For example weighing feeding identification and yield recording on cattle pigs poultry and fish. However some of these tasks still require a considerable degree of human input and more effective automation could lead to better husbandry. For example if the weight of pigs could be monitored more often without increasing labour input then this information could be used to measure growth rates and control fat level allowing accurate prediction of market dates and optimum carcass quality to be achieved with improved welfare at minimum cost. Some aspects of animal production have defied automation. For example attending to the well being of housed animals is the preserve of the expert stockman. He gathers visual data about the animals in his charge (in more plain words goes and looks at their condition and behaviour) and processes this data to draw conclusions and take actions. Automatically collecting data on well being implies that the animals are not disturbed from their normal environment otherwise false conclusions will be drawn. Computer image analysis could provide the data required without the need to disturb the animals. This paper describes new work at the Institute of Engineering Research which uses image analysis to estimate the weight of pigs as a starting point for the wider range of applications which have been identified. In particular a technique has been developed to
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
C. Patrick Schofield, C. Patrick Schofield, John A. Marchant, John A. Marchant, } "Image analysis for estimating the weight of live animals", Proc. SPIE 1379, Optics in Agriculture, (1 February 1991); doi: 10.1117/12.25092; https://doi.org/10.1117/12.25092


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