Yuheng Sun1, Ye Mu1, 2, 3, 4, *, Qin Feng5, Tianli Hu1, 2, 3, 4, He Gong1, 2, 3, 4, Shijun Li1, 2, 3, 4, Jing Zhou6
CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1317-1328, 2020, DOI:10.32604/cmc.2020.010510
Abstract In large-scale deer farming image analysis, K-means or maximum betweenclass variance (Otsu) algorithms can be used to distinguish the deer from the background.
However, in an actual breeding environment, the barbed wire or chain-link fencing has a
certain isolating effect on the deer which greatly interferes with the identification of the
individual deer. Also, when the target and background grey values are similar, the
multiple background targets cannot be completely separated. To better identify the
posture and behaviour of deer in a deer shed, we used digital image processing to
separate the deer from the background. To address the problems… More >
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