Sub-pixel straight lines detection for measuring through machine visión

Autores
Flesia, Ana; Ames, Guillermo; Bergues, Guillermo; Canali, Luis; Schurrer, Clemar
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
External visual interfaces for high precision mea suring devices are based on the segmentation of images of their measuring reticle. In this paper, a method for subpixel straight lines detection is presented and tested on images taken from the reticle of a dark field autocollimator. The method has three steps, the sharpening of the image using a version of the Savitzky-Golay filter for smoothing and differentiation, the construction of a coarse edge image using Sobel filters, and finally, the subpixel edge location determination, by fitting a Gaussian function to orthogonal sections of the coarse edge image. We discuss results of applying the proposed method to images of the reticle of a Nikon 6D autocollimator, using the scale of the device as a benchmark for testing the error in the location of the lines and comparethem with Sobel/Hough and Sobel/polynomial fitting. We report that for this type of image-content, Gaussian fitting has smaller uncertainty, when cameras with two different sensors are used.
Fil: Flesia, Ana. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Concejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Ames, Guillermo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Bergues, Guillermo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Canali, Luis. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Schurrer, Clemar. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación y Transferencia en Metrología; Argentina.
Materia
Savitzky - Goaly filter
smoothing
differentiation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Attribution-NonCommercial-NoDerivatives 4.0 International
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/14136
Acceder
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network_acronym_str RIAUTN
repository_id_str a
network_name_str Repositorio Institucional Abierto (UTN)
spelling Sub-pixel straight lines detection for measuring through machine visiónFlesia, AnaAmes, GuillermoBergues, GuillermoCanali, LuisSchurrer, ClemarSavitzky - Goaly filtersmoothingdifferentiationExternal visual interfaces for high precision mea suring devices are based on the segmentation of images of their measuring reticle. In this paper, a method for subpixel straight lines detection is presented and tested on images taken from the reticle of a dark field autocollimator. The method has three steps, the sharpening of the image using a version of the Savitzky-Golay filter for smoothing and differentiation, the construction of a coarse edge image using Sobel filters, and finally, the subpixel edge location determination, by fitting a Gaussian function to orthogonal sections of the coarse edge image. We discuss results of applying the proposed method to images of the reticle of a Nikon 6D autocollimator, using the scale of the device as a benchmark for testing the error in the location of the lines and comparethem with Sobel/Hough and Sobel/polynomial fitting. We report that for this type of image-content, Gaussian fitting has smaller uncertainty, when cameras with two different sensors are used.Fil: Flesia, Ana. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Concejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Ames, Guillermo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.Fil: Bergues, Guillermo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.Fil: Canali, Luis. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.Fil: Schurrer, Clemar. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación y Transferencia en Metrología; Argentina.Institute of Electrical and Electronics Engineers2025-11-05T20:29:53Z2014info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdf978-1-4673-6386-0https://hdl.handle.net/20.500.12272/14136enginfo:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Luis Rafael Canalireponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-10-01T11:56:48Zoai:ria.utn.edu.ar:20.500.12272/14136instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-10-01 11:56:48.947Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv Sub-pixel straight lines detection for measuring through machine visión
title Sub-pixel straight lines detection for measuring through machine visión
spellingShingle Sub-pixel straight lines detection for measuring through machine visión
Flesia, Ana
Savitzky - Goaly filter
smoothing
differentiation
title_short Sub-pixel straight lines detection for measuring through machine visión
title_full Sub-pixel straight lines detection for measuring through machine visión
title_fullStr Sub-pixel straight lines detection for measuring through machine visión
title_full_unstemmed Sub-pixel straight lines detection for measuring through machine visión
title_sort Sub-pixel straight lines detection for measuring through machine visión
dc.creator.none.fl_str_mv Flesia, Ana
Ames, Guillermo
Bergues, Guillermo
Canali, Luis
Schurrer, Clemar
author Flesia, Ana
author_facet Flesia, Ana
Ames, Guillermo
Bergues, Guillermo
Canali, Luis
Schurrer, Clemar
author_role author
author2 Ames, Guillermo
Bergues, Guillermo
Canali, Luis
Schurrer, Clemar
author2_role author
author
author
author
dc.subject.none.fl_str_mv Savitzky - Goaly filter
smoothing
differentiation
topic Savitzky - Goaly filter
smoothing
differentiation
dc.description.none.fl_txt_mv External visual interfaces for high precision mea suring devices are based on the segmentation of images of their measuring reticle. In this paper, a method for subpixel straight lines detection is presented and tested on images taken from the reticle of a dark field autocollimator. The method has three steps, the sharpening of the image using a version of the Savitzky-Golay filter for smoothing and differentiation, the construction of a coarse edge image using Sobel filters, and finally, the subpixel edge location determination, by fitting a Gaussian function to orthogonal sections of the coarse edge image. We discuss results of applying the proposed method to images of the reticle of a Nikon 6D autocollimator, using the scale of the device as a benchmark for testing the error in the location of the lines and comparethem with Sobel/Hough and Sobel/polynomial fitting. We report that for this type of image-content, Gaussian fitting has smaller uncertainty, when cameras with two different sensors are used.
Fil: Flesia, Ana. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Concejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Ames, Guillermo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Bergues, Guillermo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Canali, Luis. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Schurrer, Clemar. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación y Transferencia en Metrología; Argentina.
description External visual interfaces for high precision mea suring devices are based on the segmentation of images of their measuring reticle. In this paper, a method for subpixel straight lines detection is presented and tested on images taken from the reticle of a dark field autocollimator. The method has three steps, the sharpening of the image using a version of the Savitzky-Golay filter for smoothing and differentiation, the construction of a coarse edge image using Sobel filters, and finally, the subpixel edge location determination, by fitting a Gaussian function to orthogonal sections of the coarse edge image. We discuss results of applying the proposed method to images of the reticle of a Nikon 6D autocollimator, using the scale of the device as a benchmark for testing the error in the location of the lines and comparethem with Sobel/Hough and Sobel/polynomial fitting. We report that for this type of image-content, Gaussian fitting has smaller uncertainty, when cameras with two different sensors are used.
publishDate 2014
dc.date.none.fl_str_mv 2014
2025-11-05T20:29:53Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 978-1-4673-6386-0
https://hdl.handle.net/20.500.12272/14136
identifier_str_mv 978-1-4673-6386-0
url https://hdl.handle.net/20.500.12272/14136
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
Luis Rafael Canali
eu_rights_str_mv openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
Luis Rafael Canali
dc.format.none.fl_str_mv pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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score 13.364332

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