A computer algorithm for scoring cow teats based on udder images
In this work, we aimed to develop a computer algorithm for detecting and scoring cow teats according to udder images. In addition, by assessing three teat traits, i.e. the length, thickness, and placements, we scored them according to international standards. By applying the algorithm to 71 cows, we...
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| Veröffentlicht in: | New Zealand journal of agricultural research Jg. 68; H. 7; S. 1696 - 1706 |
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Taylor & Francis
02.12.2025
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| Abstract | In this work, we aimed to develop a computer algorithm for detecting and scoring cow teats according to udder images. In addition, by assessing three teat traits, i.e. the length, thickness, and placements, we scored them according to international standards. By applying the algorithm to 71 cows, we were able to detect all four teats in 62 of 71 (85%) cow udder images, and differentiate the front and rear teats in 56 of 62 (92%) udder images. Based on the three teat traits, we scored the teats of 56 cows. The final teat score was given by averaging the three scores for each cow. We discuss the limitations of the algorithm, and also the issues with teat conformation and image-taking itself, e.g. teats not facing perpendicular to the camera. In conclusion, we have developed the first computerised teat scoring system based on cow udder images. Further improvements require tuning parameters of the workflow and the image-taking process. |
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| AbstractList | In this work, we aimed to develop a computer algorithm for detecting and scoring cow teats according to udder images. In addition, by assessing three teat traits, i.e. the length, thickness, and placements, we scored them according to international standards. By applying the algorithm to 71 cows, we were able to detect all four teats in 62 of 71 (85%) cow udder images, and differentiate the front and rear teats in 56 of 62 (92%) udder images. Based on the three teat traits, we scored the teats of 56 cows. The final teat score was given by averaging the three scores for each cow. We discuss the limitations of the algorithm, and also the issues with teat conformation and image-taking itself, e.g. teats not facing perpendicular to the camera. In conclusion, we have developed the first computerised teat scoring system based on cow udder images. Further improvements require tuning parameters of the workflow and the image-taking process. ABSTRACT In this work, we aimed to develop a computer algorithm for detecting and scoring cow teats according to udder images. In addition, by assessing three teat traits, i.e. the length, thickness, and placements, we scored them according to international standards. By applying the algorithm to 71 cows, we were able to detect all four teats in 62 of 71 (85%) cow udder images, and differentiate the front and rear teats in 56 of 62 (92%) udder images. Based on the three teat traits, we scored the teats of 56 cows. The final teat score was given by averaging the three scores for each cow. We discuss the limitations of the algorithm, and also the issues with teat conformation and image‐taking itself, e.g. teats not facing perpendicular to the camera. In conclusion, we have developed the first computerised teat scoring system based on cow udder images. Further improvements require tuning parameters of the workflow and the image‐taking process. |
| Author | Ho, Harvey Nordbø, Øyvind Chuah, Chong Sheng |
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| Snippet | In this work, we aimed to develop a computer algorithm for detecting and scoring cow teats according to udder images. In addition, by assessing three teat... ABSTRACT In this work, we aimed to develop a computer algorithm for detecting and scoring cow teats according to udder images. In addition, by assessing three... |
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| SubjectTerms | agricultural research algorithms cameras computers Cow udder cows image processing New Zealand scoring system teat udders |
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| Title | A computer algorithm for scoring cow teats based on udder images |
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