ANN-driven edge point selection criterion
Marco Accame, Francesco G. B. De Natale, Daniele Giusto · 2002
This paper presents a new strategy that exploits artificial neural networks (ANNs) for a direct selection of edge points from an image. First, a spatial filtering for edge enhancement (the Canny filter) is used to obtain a set of candidate edge points which turn out to be the local maxima of the filtered image (MPS). A preliminary coarse selection of these points that exploits neighborhood information is performed to produce an extended pseudo-edges set (PES). Then, a features vector is extracted from the PES and is used by a neural classifier to decide whether or not a point belongs to the target edge set (TES).