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29 March 1988 Representation And Recognition Of Elongated Regions In Aerial Images
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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.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles A. Lipari, Charles A. Harlow, and Mohan M. Trivedi "Representation And Recognition Of Elongated Regions In Aerial Images", Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); https://doi.org/10.1117/12.947020
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