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Berzal Rubio, Miguel and Gómez, E. and Vicente Oliva, Jesús de and Caja García, Jesús and Barajas Fernandez, Cintia (2017). Bayesian model for subpixel uncertainty determination in optical measurements. "Procedia Manufacturing", v. 13 ; pp. 442-449. ISSN 2351-9789. https://doi.org/10.1016/j.promfg.2017.09.042.
Title: | Bayesian model for subpixel uncertainty determination in optical measurements |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | Procedia Manufacturing |
Date: | 2017 |
ISSN: | 2351-9789 |
Volume: | 13 |
Subjects: | |
Freetext Keywords: | subpixel approximation; bayesian probability; optical measurement; uncertainty; Monte Carlo method |
Faculty: | E.T.S.I. Industriales (UPM) |
Department: | Física Aplicada e Ingeniería de Materiales |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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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.
Type | Code | Acronym | Leader | Title |
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Government of Spain | DPI2016-78476-P | Unspecified | Unspecified | Desarrollo colaborativo de patrones de software y estudios de trazabilidad e intercomparación en la caracterización metrológica de superficies |
Item ID: | 53331 |
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DC Identifier: | https://oa.upm.es/53331/ |
OAI Identifier: | oai:oa.upm.es:53331 |
DOI: | 10.1016/j.promfg.2017.09.042 |
Official URL: | https://www.sciencedirect.com/science/article/pii/S2351978917306777 |
Deposited by: | Memoria Investigacion |
Deposited on: | 10 Jan 2019 19:27 |
Last Modified: | 10 Jan 2019 19:27 |