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Proceedings Paper

Feature extraction, image segmentation, and scene reconstruction
Author(s): Eric D. Lester; Ross T. Whitaker; Mongi A. Abidi
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Paper Abstract

This paper presents a scene reconstruction system that takes a pair of register range and intensity images, extracts features from both images to create feature maps, fuses these feature maps, segments the fused image, and fits surfaces to the objects in the scenes. The feature extraction locates both step edges and crease edges from the data. Edges are extracted from the intensity image using the gradient magnitude and crease edges are extracted from the range image using the gradient of the surface normal Dempster-Shafer fusion is performed on the resulting feature maps. Image segmentation is performed using a morphological watershed algorithm. Finally three-dimensional planes, spheres, and cylinders are fit to regions in the segmented scene by a least-squares optimization process.

Paper Details

Date Published: 22 September 1997
PDF: 11 pages
Proc. SPIE 3209, Sensor Fusion and Decentralized Control in Autonomous Robotic Systems, (22 September 1997); doi: 10.1117/12.287644
Show Author Affiliations
Eric D. Lester, Univ. of Tennessee/Knoxville (United States)
Ross T. Whitaker, Univ. of Tennessee/Knoxville (United States)
Mongi A. Abidi, Univ. of Tennessee/Knoxville (United States)

Published in SPIE Proceedings Vol. 3209:
Sensor Fusion and Decentralized Control in Autonomous Robotic Systems
Paul S. Schenker; Gerard T. McKee, Editor(s)

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