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Automatic body condition scoring system for dairy cows based on depth-image analysis

International Journal of Agricultural and Biological Engineering 2020年第4期13卷 45-54页

作者： Kaixuan Zhao Anthony N.Shelley Daniel L.Lau karmella a.dolecheck Jeffrey M.Bewley College of Agricultural Equipment Engineering Henan University of Science and TechnologyLuoyang 471023China Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture Ministry of Agriculture andRural AffairsHangzhou 310058China College of Biosystems Engineering and Food Science Zhejiang UniversityHangzhou 310058China Department of Electrical Engineering University of KentuckyLexington 40546USA Department of Animal and Food Sciences University of KentuckyLexington 40546USA Alltech Inc. Nicholasville 40356USA

Body condition score(BCS)is an important management tool in the modern dairy industry,and one of the basic techniques for animal welfare and precision dairy *** objective of this study was to use a vision system to evaluate the fat cover on the back of cows and to automatically determine BCS.A 3D camera was used to capture the depth images of the back of cows twice a day as each cow passed beneath the *** background subtraction,the back area of the cow was extracted from the depth *** thurl,sacral ligament,hook bone,and pin bone were located via depth image analysis and evaluated by calculating their visibility and curvature,and those four anatomical features were used to measure fatness.A dataset containing 4820 depth images of cows with 7 BCS levels was built,among which 952 images were used as training *** four anatomical features as input and BCS as output,decision tree learning,linear regression,and BP network were calibrated on the training dataset and tested on the entire *** average,the BP network model scored each cow within 0.25 BCS points compared to their manual scores during the study *** measured values of visibility and curvature used in this study have strong correlations with BCS and can be used to automatically assess BCS with high *** study demonstrates that the automatic body condition scoring system has the possibility of being more accurate than human scoring.

关键词： body condition score depth-image processing curvature analysis machine learning precision dairy farming

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