Estrus Detection Using Background Image Subtraction Technique In Tie-Stalled Cows

Simple Summary With increasing herd sizes and labor costs in recent decades, visual estrus detection by farmers has become more difficult because of the reduced manpower input per cow. To address this problem, various wearable devices have been developed for automatic estrus detection in cows, such as neck- or leg-mounted activity meters for monitoring estrus-associated increments in the amount of activity. However, these animal-contact devices have several limitations; namely, it can be dangerous to attach or remove the device and it can cause discomfort. Recently, a background image subtraction technique has been proposed as a non-contact method for monitoring activity changes in livestock animals. In this study, a new method was developed by combining the background subtraction technique and the thresholding method to detect estrus-associated activity increases in tie-stalled cows. Using this method, a substantial increase in activity in estrus was detectable, and the estrus detection sensitivity reached as high as 90% with a precision of 50%, where the sensitivity and precision were calculated as: (true-positive/[true-positive + false-negative]) x 100% and (true-positive/[true-positive + false-positive]) x 100%, respectively. This result may indicate that activity monitoring using the background subtraction technique has the potential to be a non-contact estrus detection method in tie-stalled cows. In this study, we determined the applicability of the background image subtraction technique to detect estrus in tie-stalled cows. To investigate the impact of the camera shooting direction, webcams were set up to capture the front, top, and rear views of a cow simultaneously. Video recording was performed for a total of ten estrous cycles in six cows. Standing estrus was confirmed by testing at 6 h intervals. From the end of estrus, transrectal ultrasonography was performed every 2 h to confirm ovulation time. Foreground objects (moving objects) were extracted in the videos using the background subtraction technique, and the pixels were counted at each frame of five frames-per-second sequences. After calculating the hourly averaged pixel counts, the change in values was expressed as the pixel ratio (total value during the last 24 h/total value during the last 24 to 48 h). The mean pixel ratio gradually increased at approximately 48 h before ovulation, and the highest value was observed at estrus, regardless of the camera shooting direction. When using front-view videos with an appropriate threshold, estrus was detected with 90% sensitivity and 50% precision. The present method in particular has the potential to be a non-contact estrus detection method for tie-stalled cows.