Weight Estimation of Pigs Using Top-View Image Processing

被引:9
|
作者
Kashiha, Mohammadamin [1 ]
Bahr, Claudia [1 ]
Ott, Sanne [2 ,3 ]
Moons, Christel P. H. [2 ]
Niewold, Theo A. [3 ]
Odberg, Frank O. [2 ]
Berckmans, Daniel [1 ]
机构
[1] Katholieke Univ Leuven, Dept Biosyst, M3 BIORES Measure Model & Manage Bioresponses, Kasteelpk Arenberg 30, B-3001 Louvain, Belgium
[2] Univ Ghent, Dept Anim Nutr Genet Breeding & Ethol, B-9820 Ghent, Belgium
[3] Katholieke Univ Leuven, Dept Biosystems, Div Livestock Nutr Qual, B-3001 Louvain, Belgium
关键词
Top-view body area; Pig weight estimation; Automated Image Processing; Transfer function modelling; Ellipse fitting; GROWTH; CONFORMATION; SYSTEM;
D O I
10.1007/978-3-319-11758-4_54
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:496 / 503
页数:8
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