This demo showcases a reverse image search algorithm which performs 2D affine transformation-invariant partial image-matching in sublinear time. The algorithm compares an input image to its database of preprocessed images and determines if the input matches any image in the database. The database need not contain the original image as inputs can be matched to any 2D affine transformation of the original. This means that images which have been scaled (uniformly or non-uniformly), skewed, translated, cropped or rotated (or have undergone any combination of these transformations) can be identified as coming from the same source image (Figure 1).

The algorithm runs in sublinear time with respect to the number of images in the database regardless of the number of transformations applied. Note that if image-matching could not be done in sublinear time it would not function at the scale that the likes of Google or Microsoft require.