Paper
29 March 1988 Geometry Guided Segmentation Of Outdoor Scenes
D. C. Baker, J. K. Aggarwal, S. S. Hwang
Author Affiliations +
Abstract
Many techniques for segmenting images in the absence of domain specific knowledge have been described, all with marginal success. Such an approach has been shown to be intractable. In this paper, we examine a concept bridging the gap between segmentation limitations and interpretation capabilities. In incremental segmentation, no attempt is made to obtain a complete, albeit error prone, segmentation. Instead, various heuristics are used to obtain a segmentation for the most prominent features in the image. This incomplete segmentation is forwarded to the interpretation system for initial hypothesis generation. Based on the hypotheses thus generated, the interpretation system requests the generation of additional segmentation activity to verify each hypothesis. This paper deals with determining the most prominent features in only one sense; namely those features that probably represent man-made objects in outdoor non-urban scenes. Here we provide more detail on geometric guidance. KEYWORDS: segmentation, incremental segmentation, geometric structure, line structure, 2-D description.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
D. C. Baker, J. K. Aggarwal, and S. S. Hwang "Geometry Guided Segmentation Of Outdoor Scenes", Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); https://doi.org/10.1117/12.947022
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Image segmentation

Bridges

Artificial intelligence

Colorimetry

Computer vision technology

Edge detection

Machine vision

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