DocumentCode
2497577
Title
3D-measurement of geometrical shapes by photogrammetry and neural networks
Author
Lilienblum, Tilo ; Albrecht, Peter ; Michaelis, Bernd
Author_Institution
Inst. for Measure. & Electron., Otto-von-Guericke Univ. Magdeburg, Germany
Volume
4
fYear
1996
fDate
25-29 Aug 1996
Firstpage
330
Abstract
A method is introduced which couples the classical estimation of 3D-coordinates with processing in an artificial neural network (ANN). The ANN is used to reduce the random and systematic errors of the measurement values by a-priori knowledge. The calculated geometrical shape is more precise than the results obtained with other methods or needs fewer measurement values. To calculate the weights suitable algorithms are used. It is possible to measure special dimensions of parts of measurement objects
Keywords
image recognition; neural nets; photogrammetry; 3D-coordinates; 3D-measurement; geometrical shapes; neural networks; photogrammetry; Artificial neural networks; Associative memory; Cameras; Coordinate measuring machines; Image reconstruction; Industrial training; Mathematical model; Neural networks; Position measurement; Shape measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location
Vienna
ISSN
1051-4651
Print_ISBN
0-8186-7282-X
Type
conf
DOI
10.1109/ICPR.1996.547440
Filename
547440
Link To Document