NON-CONTACT BODY CONDITION SCORE OF DAIRY COWS BASED ON TOF-TECHNOLOGY

The paper presents the results of applying the body condition score (BCS) least squares algorithm used to assess the body condition of dairy cows with a 3D ToF camera. The authors propose a method for collecting field data on the body condition of dairy cows in industrial milk production using a 3D ToF camera. The camera was installed at a height of 2200 mm from the floor at an angle of 5° towards the sacrum. Four areas of the body of 34 dairy cows were examined: the ischial tuberosities, the roundness of the maclugs, the sacral ligament, and the caudal ligament. Data were collected during milking. 136 images were processed. Digital data were processed in three types of images: in the RGB-D color spectrum, Point Cloud and binary. The assessment took into account five groups of fatness: 1 -lean; 2 - thin; 3 - well-fed; 4 - very well-fed; 5 - obese dairy cow. The resulting images were analyzed using software developed in the Matlab environment. The results of the algorithm were compared with the expert assessment of four specialists. According to the results of the BCS assessment of the algorithm, the fatness scores of groups 1 and 5 coincided with the opinion of experts with a probability of 73 and 67%, in groups 2, 3, 4 the coincidence was 61, 52 and 55%, respectively. The authors suppose that the inaccuracy in determining the fatness of groups 2, 3 and 4 is associated with their implicit differences. It is concluded that of all the BCS groups, the system more accurately determines the fatness of cows of groups 1 and 5, as well as from three image options (Point cloud 3D, RGB-D, binary) RGB-D most accurately determined the fatness of cows.

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