אסיף מאגר המחקר החקלאי

Automatic lameness detection based on consecutive 3D-video recordings

Year:

2014

Source of publication :

Authors :

Volume :

119

Co-Authors:

Van Hertem, T., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), The Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel, Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30 - bus 2456, BE-3001 Leuven, Belgium
Viazzi, S., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30 - bus 2456, BE-3001 Leuven, Belgium
Steensels, M., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), The Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel, Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30 - bus 2456, BE-3001 Leuven, Belgium
Maltz, E., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), The Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Antler, A., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), The Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Alchanatis, V., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), The Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Schlageter-Tello, A.A., WageningenUR Livestock Research, P.O. Box 65, NL-8200AB Lelystad, Netherlands
Lokhorst, K., WageningenUR Livestock Research, P.O. Box 65, NL-8200AB Lelystad, Netherlands
Romanini, E.C.B., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30 - bus 2456, BE-3001 Leuven, Belgium
Bahr, C., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30 - bus 2456, BE-3001 Leuven, Belgium
Berckmans, D., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30 - bus 2456, BE-3001 Leuven, Belgium
Halachmi, I., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), The Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel

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Abstract:

Manual locomotion scoring for lameness detection is a time-consuming and subjective procedure. Therefore, the objective of this study is to optimise the classification output of a computer vision based algorithm for automated lameness scoring. Cow gait recordings were made during four consecutive night-time milking sessions on an Israeli dairy farm, using a 3D-camera. A live on-the-spot assessed 5-point locomotion score was the reference for the automatic lameness score evaluation. A dataset of 186 cows with four automatic lameness scores and four live locomotion score repetitions was used for testing three different classification methods.The analysis of the automatic scores as independent observations led to a correct classification rate of 53.0% on a 5-point level scale. A multinomial logistic regression model based on four individual consecutive measures obtained a correct classification rate of 60.2%. When allowing a 1 unit error on the 5-point level scale, a correct classification rate of 90.9% was obtained. Strict binary classification to Lame vs. Not-Lame categories reached 81.2% correct classification rate.The use of cow individual consecutive measurements improved the correct classification rate of an automatic lameness detection system. © 2014 IAgrE.

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