ANN-driven edge point selection criterion

Author

Accame, Marco ; De Natale, Francesco G. ; Giusto, Daniele D.

Author_Institution

Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy

Volume

1

fYear

1996

fDate

16-19 Sep 1996

Firstpage

849

Abstract

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)

Keywords

edge detection; feature extraction; filtering theory; multilayer perceptrons; spatial filters; Canny filter; artificial neural networks; candidate edge points; edge enhancement; extended pseudo-edges set; features vector extraction; image edge point selection criterion; local maxima; multilayer perceptron; neighborhood information; neural classifier; preliminary coarse selection; spatial filtering; target edge set; Data mining; Detectors; Electronic mail; Filtering; Filters; Hysteresis; Image analysis; Image edge detection; Layout; Object detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1996. Proceedings., International Conference on

Conference_Location

Lausanne

Print_ISBN

0-7803-3259-8

Type

conf

DOI

10.1109/ICIP.1996.559632

Filename

559632