This article addresses the problem of two- and higher dimensional pattern matching, i.e. the identification of instances of a template within a larger signal space, which is a form of registration. Unlike traditional correlation, we aim at obtaining more selective matchings by considering more strict comparisons of gray-level intensity. In order to achieve fast matching, a nonlinear thresholded version of the fast Fourier transform is applied to a gray-level decomposition of the original 2D image. The potential of the method is substantiated with respect to real data involving the selective identification of neuronal cell bodies in gray-level images.
@article{arxiv.cs/0604094,
title = {A Fast and Accurate Nonlinear Spectral Method for Image Recognition and Registration},
author = {Luciano da Fontoura Costa and Erik Bollt},
journal= {arXiv preprint arXiv:cs/0604094},
year = {2007}
}