Cow Behavioral Recognition Using Dynamic Analysis

文献类型: 外文期刊

第一作者: Gao Ronghua

作者: Gao Ronghua;Gu JingQiu;Liang Jubao;Gao Ronghua;Gu JingQiu;Liang Jubao;Gao Ronghua;Gu JingQiu;Liang Jubao;Gao Ronghua;Gu JingQiu;Liang Jubao

作者机构:

关键词: object segmentation;image entropy;image moment;intelligent analysis

期刊名称:2017 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA)

ISSN:

年卷期: 2017 年

页码:

收录情况: SCI

摘要: The application of internet of things in dairy cattle large-scale breeding accumulates many video surveillance data. How to explore the value of dairy cow health reproductive behavior is important to scientifically formulate large-scale feeding measures and can also improve the economic benefits of dairy breeding. A cow behavioral recognition method using dynamic analysis is raised in this paper. The method focuses on the cow behavioral identification problem such as estrus and hoof disease under complex background. The abnormal behaviors that affect the healthy reproduction of dairy cows are captured based on behavior image characteristic analysis. The results show that the new method could improve the accuracy of the characteristic behavior identification, save the time of breeding staff, and improve the management efficiency of large-scale breeding.

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