Corner Detection

Corner detection, the process of identifying and locating corners in images, is crucial for various computer vision tasks, aiming for accurate and robust corner localization even under challenging conditions like noise, distortion, and varying illumination. Current research emphasizes deep learning approaches, particularly convolutional neural networks (CNNs), often incorporating multi-scale analysis and post-processing techniques like non-maximum suppression to refine results. These advancements improve accuracy and robustness in applications ranging from autonomous driving (detecting vehicle lights and lane markings) to robotics (camera calibration and pose estimation) and medical imaging (analyzing anatomical structures).