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    Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space

    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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