scale invariant feature transform (SIFT ) - rugbyprof/5443-Data-Mining GitHub Wiki

scale-invariant feature transform (SIFT )

The scale-invariant feature transform (SIFT) is a thing in computer vision to detect and describe local features in images Scale Invariant Feature Transform (SIFT) is an image descriptor for image-based matching and recognition. This descriptor as well as related image descriptors are used for a large number of purposes in computer vision related to point matching between different views of a 3-D scene and view-based object recognition. The SIFT descriptor is invariant to translations, rotations and scaling transformations in the image domain and robust to moderate perspective transformations and illumination variations. Experimentally, the SIFT descriptor has been proven to be very useful in practice for image matching and object recognition under real-world conditions.

Reference : http://www.scholarpedia.org/article/Scale_Invariant_Feature_Transform