The Inference of Structure in Images Using Multi-local Quadrature Filters

Two techniques are presented for corner detection. First, a band of filters are applied with equal radial spatial frequency, but different orientation preferences locally in the image domain. From the energy response, a linear Fourier transform is taken to give confidence measures of both "cornerness" and "edgeness. Second, we consider a multi-local spatial separation of filters that lie on a constant radius from a point of interest. This second stage of processing allows a wider classification of image structure. As a result, we infer the presence of line end points, "L", "T", "Y" and "X" junctions using epistemic probabilities. The results are indicative of a relationship between Fourier and Spatial domain models of filtering.