Scale-Invariant Feature Transform

The Scale-Invariant Feature Transform (SIFT) is a computer vision technique that helps computers recognize objects or features in images regardless of their size or angle. It detects unique patterns or key points in an image, such as edges or textures, and describes them with detailed information. This makes it possible for systems to identify the same object even if it appears larger, smaller, rotated, or viewed from a different perspective. SIFT is widely used in tasks like object recognition, image matching, and 3D modeling because of its robustness to scale and orientation changes.