Feature detection is a process used in computer vision and image processing to identify and locate specific patterns or objects within an image. This technique helps computers recognize features such as edges, corners, and textures, which are essential for understanding the content of images. Algorithms like SIFT (Scale-Invariant Feature Transform) and Harris Corner Detection are commonly employed to extract these features. Once features are detected, they can be used for various applications, including object recognition, image stitching, and tracking. By analyzing the identified features, systems can match images, detect changes, or even classify objects, enhancing the ability of machines to interpret visual information effectively.