摘要
及时检测奶牛发情、适时人工授精、减少空怀奶牛,是奶牛养殖场增加产奶量的关键手段。针对基于运动量和体温等体征的接触式奶牛发情识别方法会造成奶牛应激反应且识别准确率不高的问题,提出了一种非接触式奶牛发情行为自动识别方法。该方法首先使用改进的高斯混合模型实现运动奶牛目标检测,然后基于颜色和纹理信息去除干扰背景,再利用Alex Net深度学习网络训练奶牛行为分类网络模型,识别奶牛爬跨行为,最终实现对奶牛发情行为的自动识别。在供试数据集上的试验结果表明,本文方法对奶牛发情的识别准确率为100%,召回率为88.24%。本文方法可应用于奶牛养殖场的日常发情监测中,为生产管理提供辅助决策。
Milk is one of the main sources for humans to obtain protein,and dairy industry is also an important pillar industry for agricultural personnel in China to increase their income. Detecting the estrus of dairy cows in time,artfical insemination them at the right time,and reducing cows’ emptiness are the key means to increase the milk production of dairy farms. As the methods of identifying dairy cow estrus based on physical signs such as activity or body temperature often cause stress reactions of cows and accuracy is also not high enough,a non-contacted automatic method for recognizing estrus behaviors of cows was proposed. In this method,an improved Gaussian mixture model to achieve target detection for moving cows was used. Then,interference images were removed based on the information of color and texture. Next,a cow behavior classification network model based on AlexNet was trained to identify cows’ mounting behavior. Finally,based on the classification model result,automatic recognition of estrus behavior of cows was realized. Experiments on the test video data sets showed that the accuracy rate of the method was 100%,and the recall rate was 88. 24%. The method can be used for daily estrus monitoring of dairy farms,and it can also provide support for decision-making of their production management. The research can also serve as a reference for the automatic recognition of other large animals’ behaviors.
作者
王少华
何东健
刘冬
WANG Shaohua;HE Dongjian;LIU Dong(College of Mechanical and Electronic Engineering,Northwest A&F University,Yangling,Shaanxi 712100,China;Key Laboratory of Agricultural Internet of Things,Ministry of Agriculture and Rural Affairs,Yangling,Shaanxi 712100,China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2020年第4期241-249,共9页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家重点研发计划项目(2017YFD0701603)
国家自然科学基金面上项目(61473235)。
关键词
奶牛
发情行为
高斯混合模型
颜色
纹理
深度学习
dairy cow
estrus behavior
Gaussian mixture model
color
texture
deep learning
