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Proceedings Paper

Resolving depth-measurement ambiguity with commercially available range imaging cameras
Author(s): Shane H. McClure; Michael J. Cree; Adrian A. Dorrington; Andrew D. Payne
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Paper Abstract

Time-of-flight range imaging is typically performed with the amplitude modulated continuous wave method. This involves illuminating a scene with amplitude modulated light. Reflected light from the scene is received by the sensor with the range to the scene encoded as a phase delay of the modulation envelope. Due to the cyclic nature of phase, an ambiguity in the measured range occurs every half wavelength in distance, thereby limiting the maximum useable range of the camera. This paper proposes a procedure to resolve depth ambiguity using software post processing. First, the range data is processed to segment the scene into separate objects. The average intensity of each object can then be used to determine which pixels are beyond the non-ambiguous range. The results demonstrate that depth ambiguity can be resolved for various scenes using only the available depth and intensity information. This proposed method reduces the sensitivity to objects with very high and very low reflectance, normally a key problem with basic threshold approaches. This approach is very flexible as it can be used with any range imaging camera. Furthermore, capture time is not extended, keeping the artifacts caused by moving objects at a minimum. This makes it suitable for applications such as robot vision where the camera may be moving during captures. The key limitation of the method is its inability to distinguish between two overlapping objects that are separated by a distance of exactly one non-ambiguous range. Overall the reliability of this method is higher than the basic threshold approach, but not as high as the multiple frequency method of resolving ambiguity.

Paper Details

Date Published: 28 January 2010
PDF: 12 pages
Proc. SPIE 7538, Image Processing: Machine Vision Applications III, 75380K (28 January 2010); doi: 10.1117/12.838786
Show Author Affiliations
Shane H. McClure, The Univ. of Waikato (New Zealand)
Michael J. Cree, The Univ. of Waikato (New Zealand)
Adrian A. Dorrington, The Univ. of Waikato (New Zealand)
Andrew D. Payne, The Univ. of Waikato (New Zealand)


Published in SPIE Proceedings Vol. 7538:
Image Processing: Machine Vision Applications III
David Fofi; Kurt S. Niel, Editor(s)

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