Name
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 |
Year | DOI | Venue |
|---|---|---|
1990 | 10.1109/ICASSP.1990.115962 | Albuquerque, NM |
Keywords | Field | DocType |
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,neural network,neural networks,image restoration,adaptive systems,matched filters,detectors,edge detection,vectors | Canny edge detector,Computer science,Edge detection,Image processing,Marr–Hildreth algorithm,Artificial intelligence,Image restoration,Artificial neural network,Detector,Computer vision,Deriche edge detector,Pattern recognition,Algorithm | Conference |
ISSN | Citations | PageRank |
1520-6149 | 7 | 0.72 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paik, J.K. | 1 | 7 | 0.72 |
| Katsaggelos, A. | 2 | 80 | 10.60 |