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Proceedings Paper

Relaxation matching of road networks in aerial images using topological constraints
Author(s): Richard C. Wilson; Edwin R. Hancock
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Paper Abstract

This paper applies novel probabilistic relaxation techniques to the problem of matching road networks in different aerial images. The problem stems both from the fusion of image information obtained at different altitudes over the same region and from the matching of road map data to image data. Feature matching is hindered by segmentation error, changes of scale or perspective and distortion of the image plane. Initially the image is segmented into the road network using a dictionary based relaxation line finder, the output of which corresponds closely with ground-truth road map data. Since the contour dictionary explicitly encodes junction structure, such features are robustly detected and provide the basis for a graph based representation of road structure. In the matching phase scale and rotation measurements are used to compute an initial match of the junctions from two images. Probabilistic relaxation is then used to update junction match probabilities in light of the topological constraints provided by the road network. The main advantage of this topological representation of constraints is that it renders the matching process robust to scale and viewpoint changes.

Paper Details

Date Published: 20 August 1993
PDF: 12 pages
Proc. SPIE 2059, Sensor Fusion VI, (20 August 1993); doi: 10.1117/12.150248
Show Author Affiliations
Richard C. Wilson, Univ. of York (United Kingdom)
Edwin R. Hancock, Univ. of York (United Kingdom)

Published in SPIE Proceedings Vol. 2059:
Sensor Fusion VI
Paul S. Schenker, Editor(s)

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