P.de Chazal, C. Huynh, D. McErlean, R.B.Reilly, T.J. Hannigan, L.M. Fleury, Automatic classification of shoeprints for use in forensic science based on the fourier transform: proceedings of the IEEE International Conference on Image Processing, Barcelona: IEEE, 2003, pp569-72
This study developed a system of automatic classification
of shoeprint images into groups belonging to the same
sole pattern. When presented with an image of a new
shoeprint the system displays a ranked sequence of
shoeprint images from the database. The shoeprint images
are ranked from best match to worst match in terms of the
pattern of the shoeprint. For this study a database of 503
shoeprint images belonging to 139 pattem groups was
established with each group containing 2 or more
examples. The pattern grouping was performed by a
panel of human experts. This designed system is a fully
automatic method and functions with minimum user
intervention. Tests of the system have shown that the first
shoeprint image displayed is a correct match 54% of the
time and that a correct match appears within the first 5%
of displayed shoeprints 75% of the time. The system has
translational and rotational invariance so that the spatial
positioning of the new shoeprint images does not have to
correspond with the spatial positioning of the shoeprint
images of the database.
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