Abstract—In modern dairy farms, calving is a very critical point in the life cycle of productive cows and has played a major role in making farm profits and welfare of cows. In this time, a tremendous number of researchers have been studied the problem of calving mostly to predict the time about to calve and to investigate calving process by using wearable sensors. Like human beings, cows also have environmental pressures by wearing sensors on their bodies sometimes may cause calving difficulties. Thus in this paper, an automatic video based cow monitoring system is proposed to reduce losses of dairy farms caused from calving problems. Specifically, this paper investigates some behaviors of cows to predict time for calving process including cow movements, tail up, stretching the legs, repeating standing and sitting. In doing so, we focus on increasing movement and tail up. Here, the inter-frame difference is used for analyzing the movement and count in every frame. In addition, by extracting the head and tail position the activity of tail up or not will be recognized so that time for calving can be estimated. Finally, the proposed method for calving is confirmed by using self-collected video sequences.
 

Index Terms—calving behavior, cow monitoring, motion feature, tail up, image processing

Cite: Kosuke Sumi, Thi Thi Zin, Ikuo Kobayashi, and Yoichiro Horii, "Framework of Cow Calving Monitoring System Using Video Images," Journal of Advances in Information Technology, Vol. 12, No. 3, pp. 240-245, August 2021. doi: 10.12720/jait.12.3.240-245

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