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Proceedings Paper

Urban aerial image understanding using symbolic data
Author(s): Henri Moissinac; Henri Maitre; Isabelle Bloch
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Paper Abstract

An image interpretation method using symbolic data is presented. This method is adapted to urban scene analysis of aerial images, where the use of a priori knowledge is very helpful since the landscape is quite complex. A structure based on graphs is introduced to manage the knowledge learned about the observed scene. This structure tends to illustrate the hierarchical levels among the available data. The key point of this structure is the management of uncertainty. For the image interpretation stage, since such images can be too complicated for only one algorithm, we introduce a method for combining several algorithms that work competitively toward a same goal. Each one provides a different solution to the question studied. Then, based on conventional data fusion decision methods, for each object, the most reliable interpretation is selected taking advantage of the most efficient algorithm for these data. This approach is experimented on an urban aerial image where several algorithms for the road network extraction are combined with the help of symbolic data provided by a simple geographic map.

Paper Details

Date Published: 30 December 1994
PDF: 12 pages
Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994);
Show Author Affiliations
Henri Moissinac, Telecom Paris, Ecole Normal Superieure, and Thomson-CSF (France)
Henri Maitre, Telecom Paris (France)
Isabelle Bloch, Telecom Paris (France)

Published in SPIE Proceedings Vol. 2315:
Image and Signal Processing for Remote Sensing
Jacky Desachy, Editor(s)

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