Articles | Volume 6, issue 1
J. Sens. Sens. Syst., 6, 145–153, 2017
https://doi.org/10.5194/jsss-6-145-2017

Special issue: Sensors and Measurement Systems 2016

J. Sens. Sens. Syst., 6, 145–153, 2017
https://doi.org/10.5194/jsss-6-145-2017
Regular research article
06 Apr 2017
Regular research article | 06 Apr 2017

Statistical characterization of evaluation strategies for fringe projection systems by means of a model-based noise prediction

Marc Fischer et al.

Viewed

Total article views: 1,757 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,296 395 66 1,757 92 91
  • HTML: 1,296
  • PDF: 395
  • XML: 66
  • Total: 1,757
  • BibTeX: 92
  • EndNote: 91
Views and downloads (calculated since 06 Apr 2017)
Cumulative views and downloads (calculated since 06 Apr 2017)

Viewed (geographical distribution)

Total article views: 1,715 (including HTML, PDF, and XML) Thereof 1,691 with geography defined and 24 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 28 Sep 2022
Download
Short summary
For optical measurement systems, camera noise is the dominant uncertainty factor when optically cooperative surfaces are measured in a stable environment. In this work it will be shown that the resulting spatial noise can be estimated by means of a noise model. The capability of this approach will be demonstrated for a fringe projection system. This provides a valuable tool for a statistical comparison of different evaluation strategies, which is shown for two different triangulation procedures.