SIFT

Scale-Invariant Feature Transform (SIFT) is a computer vision algorithm used to detect and describe local features in images. It is particularly effective in identifying keypoints that are invariant to scale and rotation, making it robust for various image transformations. SIFT extracts distinctive features from images, which can then be matched across different images, enabling tasks such as object recognition, image stitching, and 3D reconstruction. This algorithm is widely used in applications ranging from robotics to augmented reality, where accurate feature matching is crucial.