基于行为监测的疑似病猪自动化识别系统

    Automatic identification system of pigs with suspected case based on behavior monitoring

    • 摘要: 针对传统的群养猪行为观察方法的缺点,提出了1种疑似病猪行为自动监测系统。系统基于ARM平台,利用安装于猪舍排泄区的嵌入式监控设备对群养猪的排泄行为进行24 h监控,通过1种改进的运动目标检测算法和基于像素块对称特征的图像识别算法定位具有异常行为的疑似病猪,并将报警图像通过通用分组无线服务(general packet radio service)网络传送至监控中心。对一栏10头大约克夏猪的试验结果表明,病猪检测正确率为78.38%,基本达到了预期的目标。因此,该文设计的方法对我国的养殖业实施自动化监测具有一定的借鉴意义。

       

      Abstract: An automatic detection method of pigs with suspected case was proposed after analyzing the disadvantages of traditional observation methods. Based on ARM platform the embedded system was designed to monitor the excretion behavior of pigs behavior in 24 hours. When the abnormal behavior detected by the moving object detection and symmetrical pixel block image recognition algorithms took place, the relevant pig would be regarded as the suspected case and the corresponding image would be sent to the surveillance center through GPRS networks. The experiment results for 10 Yorkshire pigs showed that the detection accuracy of suspected case is 78.38%. The method and monitoring system will be helpful for improving production automation in modern pig farm.

       

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