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Optical Engineering

Fast Hough transform for automated detection of spheres in three-dimensional point clouds
Author(s): Tokunbo Ogundana; Charles Russell Coggrave; Richard Burguete; Jonathan Mark Huntley
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Paper Abstract

The calibration of 3-D optical sensors normally requires the use of a calibration artifact of known dimensions. By labeling regions within the measured point clouds as belonging to a known region of the artifact, camera and projector parameters can be optimized. A novel 3-D Hough transform has been developed to extend the well-known strategy for detecting circles in 2-D images to detecting spheres in a 3-D point cloud. In its standard form, the Hough transform suffers from excessive memory storage requirements for the intermediate Hough accumulator space, which can make its application to 3-D problems impractical. We describe an accumulator implementation using an optimized sparse 3-D matrix model that provides compact data storage and efficient data access. Application of this method to experimental shape data for spheres is discussed, demonstrating its memory-saving benefits, computational efficiency, and 3-D feature detection capability.

Paper Details

Date Published: 1 May 2007
PDF: 11 pages
Opt. Eng. 46(5) 051002 doi: 10.1117/1.2739011
Published in: Optical Engineering Volume 46, Issue 5
Show Author Affiliations
Tokunbo Ogundana, Loughborough Univ. of Technology (United Kingdom)
Charles Russell Coggrave, Phase Vision Ltd. (United Kingdom)
Richard Burguete, Airbus UK (United Kingdom)
Jonathan Mark Huntley, Loughborough Univ. of Technology (United Kingdom)


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