Abstract
A Cow’s ruminant behavior can provide information about a cow’s health. Monitoring a cow’s ruminant behavior could therefore be of use when assessing its health. However, it is difficult to simultaneously monitor multiple target cows’ ruminations simultaneously without any contact-type equipment. A method for monitoring multiple target cows’ ruminant behavior based on an optical flow method and an inter-frame difference method is proposed here in. The optical flow method is used to obtain the optical flow fields of the ruminant cows’ mouth areas in the first 60 frames of a video. The optical flow values with large changes are selected from the first 60 frames of the test video and these values are superimposed to obtain the candidate ruminant cows’ mouth areas. The candidate ruminant cows’ mouth areas are magnified 1.5 times, and the inter-frame difference method is used to track the real cows’ mouth areas in the new magnified areas. According to the “center error” and “overlap rate” indexes, the tracking result for the 15 videos is evaluated. The results show that the average successful tracking rate reaches 89.12%, demonstrating that the algorithm could be applied for the automatic monitoring of multiple target ruminant cows’ mouth areas.
Highlights
A dairy cow’s ruminant behavior is an important indicator of its health status
Reith et al proposed an automatic detection method for ruminant cows based on microphone technology and created a monitoring system [4]
Braun et al proposed an automatic detection method for ruminant cows based on a nasal pressure sensor; the pressure change during ruminant cows’ chewing was measured to count the number of ruminations using a pressure sensor fixed to the cows’ nose straps
Summary
A dairy cow’s ruminant behavior is an important indicator of its health status. When the cow is in the early stage of ruminating food, rumen hernia, traumatic network gastritis, it is difficult to diagnose these diseases by using existing medical techniques, and it is difficult to statistically analyze the duration of a cow’s rumination by manual monitoring [1]. Manual monitoring of a cow’s ruminant behavior has always been widely used, such methods require substantial time and human resources, and the monitoring results are not accurate and do not meet the demands of modern. Reith et al proposed an automatic detection method for ruminant cows based on microphone technology and created a monitoring system [4]. The final test results showed that the number of ruminations in the estrus period was, on average, reduced by 24% on average compared to cows that were not in estrus. Braun et al proposed an automatic detection method for ruminant cows based on a nasal pressure sensor; the pressure change during ruminant cows’ chewing was measured to count the number of ruminations using a pressure sensor fixed to the cows’ nose straps
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