AUTOMATED CATTLE DETECTION USING MASK R-CNN AND IOU-BASED TRACKING WITH A SINGLE SIDE-VIEW CAMERA

In precision livestock farming, the early detection of lameness in cattle is an extremely important aspect of effective breeding management. Timely identification of lameness not only facilitates prompt and cost-efficient treatment but also plays a crucial role in avoiding possible future diseases. This study emphasizes the significance of intelligent visual perception systems for lameness detection in dairy cattle, particularly in the lane between from Milking Parlor to Cattle Barn. To address the cattle lameness issue, we employ an advanced deep learning, and image processing technique, i.e., Mask R-CNN from Detectron2 to detect and identify cattle regions for feature extraction of lameness detection. On the other hand, cattle tracking using IoU is also an important part of data accumulation for lameness classification. The results of this study contribute to ongoing efforts in precision animal husbandry and demonstrate the potential of intelligent visual recognition systems for early lameness detection. © 2024, ICIC International. All rights reserved.