DocumentCode :
2709127
Title :
An edge detection scheme using radial basis function networks
Author :
De Silva, L.c. ; De Silva, L.C. ; Ranganath, Suhas
Author_Institution :
Nat. Univ. of Singapore, Singapore
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
604
Abstract :
A new edge detection scheme based on radial basis function networks is proposed. It is a two-tiered scheme where, in the first stage, each pixel in the input image is classified according to its potential for being part of an edge. The second stage then combines these pixels into true edges in the input image. Both stages use radial basis function networks. The scheme illustrates how the input space of edge patterns can be used to train the neural network with a minimum number of parameters. Compared with other neural network paradigms, the proposed scheme is simpler in terms of network size and computational requirements, and provides better results even in low-contrast images
Keywords :
edge detection; image classification; radial basis function networks; computational requirements; edge detection scheme; edge pattern input space; low-contrast images; minimum parameter number; network size; neural network training; pixel classification; pixel combination; radial basis function networks; two-tiered scheme; Associative memory; Computer networks; Detectors; Image edge detection; Lighting; Matched filters; Neural networks; Pixel; Radial basis function networks; Reflectivity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing Society Workshop
Conference_Location :
Sydney, NSW
ISSN :
1089-3555
Print_ISBN :
0-7803-6278-0
Type :
conf
DOI :
10.1109/NNSP.2000.890139
Filename :
890139
Link To Document :
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