Rotation invariant histogram filters for similarity and distance measures between digital images

Fast rotation invariant filtering algorithms are presented for speeding-up the search for the position of a given pattern template from a large image. The algorithms work for several distance/similarity measures. The algorithms give useful correlation information as such, and can be used as filtering algorithms for more sophisticated methods. The results are presented in the 2D case, but extensions to 3D are straightforward. The algorithms are based on color histograms computed from the pattern. A technique is described for pruning the filtered positions incrementally, using a simple, yet effective boundary that divides the search space in two.