Skip to main content
Presentation
Fringe calibration using neural network signal mapping for structured light profilometers
Faculty of Informatics - Papers (Archive)
  • Matthew J Baker
  • Jiangtao Xi, University of Wollongong
  • Joe F Chicharo, University of Wollongong
RIS ID
17519
Publication Date
12-12-2006
Publication Details

This paper was originally published as: Baker, MJ, Xi, J & Chicharo, JF, Fringe calibration using neural network signal mapping for structured light profilometers, International Symposium on Intelligent Signal Processing and Communications 2006 (ISPACS '06), Yonago, Japan, 12-15 December 2006, 784-787. Copyright IEEE 2006.

Abstract

We present a novel neural network signal calibration technique to improve the performance of triangulation based structured light profilometers. The performance of such profilometers is often hindered by the capture of noisy and aberrated pattern intensity distributions. We address this problem by employing neural networks and a spatial digital filter in a signal mapping approach. The performance of the calibration technique is gauged through both simulation and experimentation, with simulation results indicating that accuracy can be improved by more than 80%.

Citation Information
Matthew J Baker, Jiangtao Xi and Joe F Chicharo. "Fringe calibration using neural network signal mapping for structured light profilometers" (2006)
Available at: http://works.bepress.com/jxi/23/