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Proceedings Paper

A parallel implementation of 3D Zernike moment analysis
Author(s): Daniel Berjón; Sergio Arnaldo; Francisco Morán
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Paper Abstract

Zernike polynomials are a well known set of functions that find many applications in image or pattern characterization because they allow to construct shape descriptors that are invariant against translations, rotations or scale changes. The concepts behind them can be extended to higher dimension spaces, making them also fit to describe volumetric data. They have been less used than their properties might suggest due to their high computational cost. We present a parallel implementation of 3D Zernike moments analysis, written in C with CUDA extensions, which makes it practical to employ Zernike descriptors in interactive applications, yielding a performance of several frames per second in voxel datasets about 2003 in size. In our contribution, we describe the challenges of implementing 3D Zernike analysis in a general-purpose GPU. These include how to deal with numerical inaccuracies, due to the high precision demands of the algorithm, or how to deal with the high volume of input data so that it does not become a bottleneck for the system.

Paper Details

Date Published: 25 January 2011
PDF: 7 pages
Proc. SPIE 7872, Parallel Processing for Imaging Applications, 787209 (25 January 2011); doi: 10.1117/12.876683
Show Author Affiliations
Daniel Berjón, Univ. Politécnica de Madrid (Spain)
Sergio Arnaldo, Univ. Politécnica de Madrid (Spain)
Francisco Morán, Univ. Politécnica de Madrid (Spain)


Published in SPIE Proceedings Vol. 7872:
Parallel Processing for Imaging Applications
John D. Owens; I-Jong Lin; Yu-Jin Zhang; Giordano B. Beretta, Editor(s)

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