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Using a 3D camera to evaluate the back posture of dairy cows

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  131620172,  2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: @2013
Authors:   S Viazzi, T Van Hertem, A Schlagater-Tello, C Bahr, C EB Romanini, I Halachmi, C Lokhorst, D Berckmans
Keywords:   dairy cow lameness detection back arch image processing 3D camera

Abstract. In this study, a new computer vision technique to automatically detect lameness in dairy cows was evaluated. A 3D camera system was used to extract the back posture of the animals from top view perspective in a fully automatic way. Four parameters to describe the curvature of the back of the cows were used by a decision tree to classify lame and not lame cows. The experiment was conducted in a commercial Israeli dairy farm. The classification performance of the 3D algorithm was evaluated against the visual locomotion scores given by an expert veterinary. A dataset of 273 cows served to train the model and a dataset of 906 cows to validate it. The analysis led to a sensitivity of 67% and a specificity of 90% on a 2-point level scale (lame or not lame) on the validation dataset. These results show that the application of a 3D camera in dairy farming is feasible and can be used in order to develop a fully automatic lameness monitoring tool in dairy farming.

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