DocumentCode
3324570
Title
A neural network based recognition of complex two-dimensional objects
Author
Lauterbach, Bernd ; Besslich, P.W.
Author_Institution
Bremen Univ., Germany
fYear
1991
fDate
28 Oct-1 Nov 1991
Firstpage
2504
Abstract
The authors describe the recognition of complex two-dimensional objects using a neural network. The procedure is based on a set of image processing algorithms which produce several feature vectors. These are fed into a hierarchical structured configuration of neural networks. Most of the image processing algorithms can easily be parallelized, so that the implementation on a multiprocessor system is straightforward. The procedure has been implemented on a tree-structured transputer network
Keywords
image processing; image recognition; neural nets; parallel architectures; transputers; feature vector; hierarchical structured configuration; image processing algorithms; learning algorithm; multilayer perceptions; multiprocessor; neural network; online correction; tree-structured transputer network; two-dimensional objects; Distortion measurement; Fault tolerance; Gravity; Hardware; Image processing; Image segmentation; Length measurement; Neural networks; Quantization; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, Control and Instrumentation, 1991. Proceedings. IECON '91., 1991 International Conference on
Conference_Location
Kobe
Print_ISBN
0-87942-688-8
Type
conf
DOI
10.1109/IECON.1991.238936
Filename
238936
Link To Document