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Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image

Nowadays the automobile industry is becoming more and more demanding as far as quality is concerned. Within the wide variety of processes in which this quality must be ensured, those regarding the squeezing of the auto bodywork are especially important due to the fact that the quality of the resulti...

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Detalles Bibliográficos
Autores principales: Barber, Ramon, Zwilling, Valerie, Salichs, Miguel A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3958262/
https://www.ncbi.nlm.nih.gov/pubmed/24504105
http://dx.doi.org/10.3390/s140202476
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author Barber, Ramon
Zwilling, Valerie
Salichs, Miguel A.
author_facet Barber, Ramon
Zwilling, Valerie
Salichs, Miguel A.
author_sort Barber, Ramon
collection PubMed
description Nowadays the automobile industry is becoming more and more demanding as far as quality is concerned. Within the wide variety of processes in which this quality must be ensured, those regarding the squeezing of the auto bodywork are especially important due to the fact that the quality of the resulting product is tested manually by experts, leading to inaccuracies of all types. In this paper, an algorithm is proposed for the automated evaluation of the imperfections in the sheets of the bodywork after the squeezing process. The algorithm processes the profile signals from a retroreflective image and characterizes an imperfection. It is based on a convergence criterion that follows the line of the maximum gradient of the imperfection and gives its geometrical characteristics as a result: maximum gradient, length, width, and area.
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spelling pubmed-39582622014-03-20 Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image Barber, Ramon Zwilling, Valerie Salichs, Miguel A. Sensors (Basel) Article Nowadays the automobile industry is becoming more and more demanding as far as quality is concerned. Within the wide variety of processes in which this quality must be ensured, those regarding the squeezing of the auto bodywork are especially important due to the fact that the quality of the resulting product is tested manually by experts, leading to inaccuracies of all types. In this paper, an algorithm is proposed for the automated evaluation of the imperfections in the sheets of the bodywork after the squeezing process. The algorithm processes the profile signals from a retroreflective image and characterizes an imperfection. It is based on a convergence criterion that follows the line of the maximum gradient of the imperfection and gives its geometrical characteristics as a result: maximum gradient, length, width, and area. Molecular Diversity Preservation International (MDPI) 2014-02-05 /pmc/articles/PMC3958262/ /pubmed/24504105 http://dx.doi.org/10.3390/s140202476 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Barber, Ramon
Zwilling, Valerie
Salichs, Miguel A.
Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image
title Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image
title_full Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image
title_fullStr Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image
title_full_unstemmed Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image
title_short Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image
title_sort algorithm for the evaluation of imperfections in auto bodywork using profiles from a retroreflective image
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3958262/
https://www.ncbi.nlm.nih.gov/pubmed/24504105
http://dx.doi.org/10.3390/s140202476
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