Abstract
In this paper, we consider the use of orthogonal moments for invariant
classification of alphanumeric characters of different size. In addition
to the Zernike and pseudo-Zernike moments (ZMs and PZMs) which have
been previously proposed for invariant character recognition, a new
method of combining Orthogonal Fourier–Mellin moments (OFMMs) with
centroid bounding circle scaling is introduced, which is shown to
be useful in characterizing images with large variability. Through
extensive experimentation using ZMs and OFMMs as features, different
scaling methodologies and classifiers, it is shown that OFMMs give
the best overall performance in terms of both image reconstruction
and classification accuracy.
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