A Fast and Accurate Nonlinear Spectral Method for Image Recognition and Registration

This letter 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, the authors 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 two-dimensional 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.