DocumentCode :
2925987
Title :
Edge detection using a neural network
Author :
Paik, Joon ; Katsaggelos, Aggelos
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Northwestern Univ., Evanston, IL, USA
fYear :
1990
fDate :
3-6 Apr 1990
Firstpage :
2145
Abstract :
An edge detection algorithm using multistate ADALINES (adaptive linear neurons) is presented. The proposed algorithm can suppress noise effects without increasing the mask size. The input states are defined using the local mean in a predefined mask, and the one-dimensional edges are defined so that they are linearly separable from nonedges. The two-dimensional edges are obtained using the rotation invariant property of layered neural networks. The proposed algorithm requires much less computation compared with Marr and Hildreth´s (1980) edge detector for similar performance. An application of the proposed edge detector to adaptive image restoration is also presented
Keywords :
neural nets; picture processing; adaptive image restoration; adaptive linear neurons; edge detection algorithm; edge detector; image processing; input states; layered neural networks; local mean; rotation invariant property; Adaptive systems; Detectors; Image edge detection; Image processing; Image restoration; Laplace equations; Matched filters; Neural networks; Neurons; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.1990.115962
Filename :
115962
Link To Document :
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