Abstract
Good health is a key element in pig welfare and steady weight gain is considered an indicator of good health and productivity. Therefore, continuous weight monitoring is an essential method to ensure pigs are in good health. The purpose of this work was to investigate feasibility of an automated method to estimate weight of pigs by using image processing.
The weight estimation process developed as follows: First, to localize pigs in the image, an ellipse fitting algorithm was employed. Second, the area the pig was occupying in the ellipse was calculated. Finally, the weight of pigs was estimated using dynamic modelling. This method can replace the regular weight measurements in farms that require repeated handling and thereby causing stress to the pigs.
Overall, video imaging of fattening pigs appeared promising for real-time weight and growth monitoring. In this study the weight could be estimated with an accuracy of 97.5 % (± 0.82 kg). This result is significant since the existing automated tools currently have a maximum accuracy of 95 % (± 2 kg) in practical setups and 97 % (± 1 kg) in walk-through systems (when pigs are forced to pass a corridor one by one) on average.
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Kashiha, M. et al. (2014). Weight Estimation of Pigs Using Top-View Image Processing. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8814. Springer, Cham. https://doi.org/10.1007/978-3-319-11758-4_54
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DOI: https://doi.org/10.1007/978-3-319-11758-4_54
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