You Only Look Once v8 Cattle Identification Based on Muzzle Print Pattern Using ORB and Fast Library for Approximate Nearest Neighbor Algorithms

Cattle identification is important in livestock management, and advanced techniques are required to identify cattle without ear tagging, branding, or any identification method that harms the cattle. This study aims to develop computer vision techniques to identify cattle based on their unique muzzle print features. The developed method employed the YOLOv8 object detection model to detect the cattle’s muzzle. Following detection, the captured muzzle image underwent image processing. Contrast-limited adaptive histogram equalization (CLAHE) was used to enhance the image quality and obtain a prominent and detailed image of the muzzle print. Feature extraction algorithm-oriented FAST and rotated BRIEF (ORB) was applied to extract key points and detect descriptors that are crucial for the cattle identification process. The fast library for approximate nearest neighbor (FLANN) was also employed to identify individual cattle by comparing descriptors of query images from those stored in the database. To validate the developed method, its performance was evaluated on 25 different cattle. In total, 22 out of 25 were correctly identified, resulting in an overall accuracy of 88%.