SIFT

SIFT, or Scale-Invariant Feature Transform, is a computer vision technique used to identify and describe distinctive patterns or features in images, such as corners or edges. It recognizes these features regardless of changes in scale, rotation, or lighting, making it useful for tasks like object recognition and image matching. SIFT works by analyzing the image at multiple sizes, detecting key points, and extracting unique descriptors for each, enabling reliable comparison between different images even under different conditions. This robustness makes SIFT valuable in applications like biometric identification, 3D modeling, and visual tracking.