Edge detection is a widely used tool for identifying abrupt changes or discontinuities in a signal/digital image. It is well-known that Radial Basis Functions (RBFs) are a powerful tool in data interpolation/approximation. We discuss their use in edge detection and propose new techniques based on variably scaled kernels and on the identification of the local maxima of the absolute values of the interpolation coefficients. Some numerical examples illustrate the effectiveness of the proposed techniques.

This presentation is part of Minisymposium “MS2 - Interpolation and Approximation Methods in Imaging (4 parts)”
organized by: Alessandra De Rossi (University of Torino) , Costanza Conti (University of Firenze) , Francesco Dell'Accio (University of Calabria) .

Authors:

Milvia Rossini (University of Milano-Bicocca)

Lucia Romani (University of Milano-Bicocca)

Daniela Schenone (University of Milano-Bicocca)

Keywords:

edge detection, kernel methods, radial basis functions