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This paper proposes a technique for automatically recognising shoeprint images for use in forensic science. The method uses the Fourier-Mellin transform to produce translation, rotation and scale invariant features. A two dimensional correlation is employed as the similarity metric for the classification process. Experiments were conducted on a database of 500 different shoeprint images representing a part of available shoes on the market. In order to test the robustness of the method, test images including different perturbations such as noise addition and cropping (partial shoeprints) were generated. Experimental results show that the proposed method is very practical providing attractive performance when processing distorted shoeprint images.