Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Bayesian model for subpixel uncertainty determination in optical measurements
Year:2017
Research Areas
  • Engineering
Information
Abstract
Uncertainty determination can be obtained by two procedures: GUM and the Monte Carlo Method. This work presents a model that helps to evaluate the uncertainty in measurements collected by optical measuring machines when using the Monte Carlo method. Initially, the model converts intensity, using Bayesian probability, from the pixel image derived from camera into a polygonal area with three to five vertexes. The outer vertexes are fitted using least squares procedures to obtain a measurand shape approximation in a subpixel range. Algorithms have been programmed and verified into Matlab using synthetic images with different triangles. Through a detailed analysis, the usefulness of a new tool, the parameter, will be demonstrated as an alternative method for estimating uncertainty of measurements of pixel images.
International
Si
JCR
No
Title
Procedia Manufacturing
ISBN
2351-9789
Impact factor JCR
Impact info
Volume
13 (2017)
10.1016/j.promfg.2017.09.042
Journal number
13
From page
442
To page
449
Month
SIN MES
Ranking
SCImago Journal Rank (SJR): 0.105
Participants
  • Autor: Miguel Berzal Rubio (UPM)
  • Autor: Emilio Gomez Garcia (UPM)
  • Autor: Jesus Caja Garcia (UPM)
  • Autor: Cintia Barajas Fernandez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Metrología Dimensional
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)