1. A method of finding candidate images from a large corpus of images that at least partially match a query image, the method comprising the steps of: (a) identifying local regions of interest within the candidate and query images by a first feature detection scheme; (b) identifying local points of interest within the candidate and query images by a second feature detection scheme different than the first; (c) defining bundled features within the candidate and query images by grouping together the local points of interest that occur within a given local region of interest; (d) comparing bundled features of the query image to bundled features of a candidate image to find a bundled feature in the query image and a bundled feature in the candidate image that share at least two common local points of interest; (e) determining the relative positions of local points of interest along first and second perpendicular axes within bundles in the query image and candidate image; and (f) comparing the relative positions determined in said step (e) between bundles in the first image and the query image.