基于视频分析的奶牛呼吸频率与异常检测

Detection of Breathing Rate and Abnormity of Dairy Cattle Based on Video Analysis

为实现奶牛呼吸状态信息获取的自动化、智能化,在构建奶牛视频实时采集系统的基础上,研究并提出了奶牛呼吸频率与异常检测方法。用光流法计算视频帧图像各像素点的相对运动速度,根据各点速度,对像素点进行循环Otsu处理筛选出呼吸运动点,动态计算速度方向曲线的周期即可检测牛只呼吸频率,并根据单次呼吸耗时检测呼吸是否异常。对72头奶牛共进行360 min检测试验,结果表明,呼吸频率计算准确率为95.68%,异常检测成功率为89.06%,平均异常误检次数为2.53次/min。

A real-time video capturing system for dairy was designed,and a detection method of breathing rate and abnormity in cows was studied based on the system to acquire the information in breathing.The optical flow method was used to calculate the velocity for each pixel.Breathing points were found out by looping Otsu operation according to the magnitude of velocity.The period was calculated from the curve of direction of velocity to get the breathing rate,and breathing abnormity was detected according the duration of each breath.72 cows were detected for total 360 minutes to test the methods.The results demonstrated that the accuracy of calculated breathing rate and the recognition ratio of breathing abnormity were 95.68% and 89.06%,respectively,and the error detection of breathing abnormity was 2.53 times per-minute.