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Proceedings Paper

Region segmentation based on 3D geometry from range images
Author(s): Dongming Zhao; Jenny J. Chen; Xingjun Wang; Sean X. Zhang
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Paper Abstract

Region segmentation provides a valid information check point and background knowledge for higher level machine vision tasks that rely on the fundamental image processing and analysis results such as segmentations. Our study of segmenting regions of interest on range images shows that knowing local surface geometries becomes the key to successfully solving segmentation problems. In this paper, three topics are presented and the experiments are shown: (1) segmentation based on morphological watershed algorithm; (2) a multiscale approach using morphology; and (3) a segmentation method based on surface normals. The examples used in this study are from the range images taken by a laser radar imager. The applications are focused in the area of manufacturing automation and inspection.

Paper Details

Date Published: 18 September 1997
PDF: 12 pages
Proc. SPIE 3205, Machine Vision Applications, Architectures, and Systems Integration VI, (18 September 1997); doi: 10.1117/12.285561
Show Author Affiliations
Dongming Zhao, Univ. of Michigan/Dearborn (United States)
Jenny J. Chen, Univ. of Michigan/Dearborn (United States)
Xingjun Wang, Univ. of Michigan/Dearborn (United States)
Sean X. Zhang, Univ. of Michigan/Dearborn (United States)

Published in SPIE Proceedings Vol. 3205:
Machine Vision Applications, Architectures, and Systems Integration VI
Susan Snell Solomon; Bruce G. Batchelor; John W. V. Miller, Editor(s)

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