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Proceedings Paper

Distance recovery of 3D objects from stereo images using Hough transform
Author(s): Albert J. Parent; Patrick S. P. Wang
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Paper Abstract

This paper examines recovering the depth of an object from two stereo images by correlating matching feature points. The principle concern of this paper is to demonstrate one method of feature point extraction. The orientation of the two viewers with respect to each other is fixed, this allows us to make use of the epipolar constraint for depth recovery. The methodology for extracting feature points from each image are: perform edge detection on each original image; use the Hough transform to identify the lines which define the image; label feature points as the intersections of lines where the intersection is a valid point in the edge detected image. The above method was very accurate with respect to recovering the depth of input images which were in certain orientations. However, the algorithm was too sensitive to error in the Hough transform space to allow for consistent evaluation of depth for all orientations.

Paper Details

Date Published: 13 October 1994
PDF: 9 pages
Proc. SPIE 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, (13 October 1994); doi: 10.1117/12.189103
Show Author Affiliations
Albert J. Parent, Northeastern Univ. (United States)
Patrick S. P. Wang, Northeastern Univ. (United States)


Published in SPIE Proceedings Vol. 2354:
Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision
David P. Casasent, Editor(s)

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