A neural network based recognition of complex two-dimensional objects

A neural network based recognition of complex two-dimensional objects

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 proce...

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Bibliographische Detailangaben
Hauptverfasser: Lauterbach, B., Besslich, P.W.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Distortion measurement
Fault tolerance
Gravity
Hardware
Image processing
Image segmentation
Length measurement
Neural networks
Quantization
Shape
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Beschreibung
Zusammenfassung: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.< >
DOI:10.1109/IECON.1991.238936