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Proceedings Paper

Representation And Recognition Of Elongated Regions In Aerial Images
Author(s): Charles A. Lipari; Charles A. Harlow; Mohan M. Trivedi
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Paper Abstract

The recent advances in model-based image understanding systems for aerial imagery have used intermediate-level interpretations of the low-level segmentations in terms of generic shape properties. This paper is concerned with those features recognizable in the context of having an elongated shape as evidenced from the planar point sets obtained from spectral classifications. The basic processing technique can be described as linear-strip point clustering, using the minimum spanning tree as a connectivity constraint. The algorithms are applied to classifications of suburban road networks. The major elongated regions are detected for the given strip width, and where connectivity can be established across any gaps in the segmentation.

Paper Details

Date Published: 29 March 1988
PDF: 11 pages
Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); doi: 10.1117/12.947020
Show Author Affiliations
Charles A. Lipari, Louisiana State University (United States)
Charles A. Harlow, Louisiana State University (United States)
Mohan M. Trivedi, University of Tennessee (United States)


Published in SPIE Proceedings Vol. 0937:
Applications of Artificial Intelligence VI
Mohan M. Trivedi, Editor(s)

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