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Title: Automatic Identification of Marked Pigs in a Pen Using Image Pattern Recognition
Authors: Kashiha, Mohammadamin ×
Bahr, Claudia
Ott, Sanne
Moons, Chistel P.H.
Niewold, Theo
Ödberg, Frank O.
Berckmans, Daniel #
Issue Date: Apr-2013
Publisher: Elsevier
Series Title: Computers and Electronics in Agriculture vol:93 pages:111-120
Abstract: The purpose of this work was to investigate feasibility of an automated method to identify marked pigs in a pen in different light conditions by using image processing.
This study comprised measurements on four groups of piglets, with 10 piglets per group in a pen. On average, piglets had a weight of 27±4.4 kilograms at the start of experiments and 40kg ± 6.5 at the end. For the purpose of individual identification, basic patterns were painted on the back of the pigs. Each pen was monitored by a top-view CCD camera.
Ellipse fitting algorithms were employed to localise pigs. Consequently, individual pigs could be identified by their respective paint pattern using pattern recognition techniques. Taking visual labelling of videos by an experienced ethologist as the gold standard, pigs could be identified with an average accuracy of 89.4%. It was also shown that behaviours such as resting can be monitored using the presented technique.
ISSN: 0168-1699
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Livestock-Nutrition-Quality
Division M3-BIORES: Measure, Model & Manage Bioresponses
× corresponding author
# (joint) last author

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