Title: Performance of an Image Analysis Processing System for Hen Tracking in an Environmental Preference Chamber
Authors: Kashiha, Mohammadamin ×
Green, Angela R.
Sales, Tatiana Glogerley #
Bahr, Claudia
Berckmans, Daniel #
Gates, Richard S. #
Issue Date: 2014
Publisher: Poultry Science Association
Series Title: Poultry Science
Article number: 4078
Abstract: Image processing systems have been widely used in monitoring livestock for many applications, including identification, tracking, behavior analysis, occupancy rates and activity calculations. The primary goal of this work was to quantify image processing performance when monitoring laying hens by comparing length of stay in each compartment as detected by the image processing system with the actual occurrences registered by human observations. In this work, an image processing system was implemented and evaluated for use in an Environmental Animal Preference Chamber to detect hen navigation between four compartments of the chamber. One camera was installed above each compartment to produce top-view images of the whole compartment. An ellipse-fitting model was applied to captured images to detect whether the hen was present in a compartment. During a choice-test study, mean ± SD success detection rates of 95.9 ± 2.6% were achieved when considering total duration of compartment occupancy. These results suggest that the image processing system is currently suitable for determining the response measures for assessing environmental choices. Moreover, the image processing system offered a comprehensive analysis of occupancy while substantially reducing data processing time compared to the time-intensive alternative of manual video analysis. The above technique was used to monitor ammonia aversion in the chamber. As a preliminary pilot study, different levels of ammonia were applied to different compartments while hens were allowed to navigate between compartments. Using the automated monitor tool to assess occupancy, a negative trend of compartment occupancy with ammonia level was revealed, though further examination is needed.
ISSN: 0032-5791
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division M3-BIORES: Measure, Model & Manage Bioresponses (-)
× corresponding author
# (joint) last author

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