ЗАВДАННЯ ЗІСТАВЛЕННЯ ЗОБРАЖЕНЬ ТА ПОБУДОВА SIFT ДЕСКРИПТОРІВ

This study investigates the efficacy of detecting key points in images using a method based on Gaussian pyramids and differences. Key points are identified based on local extrema in the Gaussian pyramid levels, and their orientations are determined by analyzing gradient directions in the vicinity. A descriptor is then computed for each key point to provide a compact representation of its local features. These descriptors, computed on Gaussian-smoothed images, enable robustness to rotations. Despite their versatility, these descriptors may encounter limitations in scenarios involving repetitive patterns or reflections. Nevertheless, they find wide applicability in various image analysis tasks.