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Proceedings Paper

Artificial neural networks for photogrammetric target processing
Author(s): W. C. Chiu; E. L. Hines; C. Forno; R. Hunt; S. Oldfield
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Paper Abstract

The ultimate aim of this work is to produce a control system for two dimensional measuring machines which will be capable of automatically seeking and finding 'target' images on photogram- metric plates, giving accurate estimates of the co-ordinates of the centres of the target and some objec- tive measure of the uncertainty of these estimates. It is well known that the target locating process is labour intensive, generally requiring days of work for operators to identify several thousand targets contained in a photogrammetric plate. Even using sophisticated image processing techniques, the scanning system still suffers from slow operating speed, intensive programming requirements and not being capable of adapting to different types of target. In order to minimise these deficiencies, an artificial neural network approach has been employed to develop the automatic scanning system. This paper describes the progress made on this application of artificial neural networks.

Paper Details

Date Published: 1 August 1990
PDF: 8 pages
Proc. SPIE 1395, Close-Range Photogrammetry Meets Machine Vision, 13952U (1 August 1990); doi: 10.1117/12.2294345
Show Author Affiliations
W. C. Chiu, Univ. of Warwick (United Kingdom)
E. L. Hines, Univ. of Warwick (United Kingdom)
C. Forno, National Physical Lab. (United Kingdom)
R. Hunt, National Physical Lab. (United Kingdom)
S. Oldfield, National Physical Lab. (United Kingdom)


Published in SPIE Proceedings Vol. 1395:
Close-Range Photogrammetry Meets Machine Vision
Armin Gruen; Emmanuel P. Baltsavias, Editor(s)

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