Dataset for defect detection in textile manufacturing

Artículo de datos

Detalhes bibliográficos
Autores: Gil Arroyo, Beatriz, Marcos Sanz, Juan, Arroyo Puente, Ángel, Urda Muñoz, Daniel, Basurto Hornillos, Nuño, Herrero Cosío, Álvaro
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Recursos:Universidad de Burgos (UBU)
Repositorio:Repositorio Institucional de la Universidad de Burgos (RIUBU)
OAI Identifier:oai:riubu.ubu.es:10259/10545
Acesso em linha:https://hdl.handle.net/10259/10545
Access Level:acceso abierto
Palavra-chave:Textile manufacturing
Textile industry
Batavia and Sarga fabric
Defect detection
Image analysis
Artificial vision
Quality inspection
Inteligencia artificial
Industria textil
Artificial intelligence
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spelling Dataset for defect detection in textile manufacturingGil Arroyo, BeatrizMarcos Sanz, JuanArroyo Puente, ÁngelUrda Muñoz, DanielBasurto Hornillos, NuñoHerrero Cosío, ÁlvaroTextile manufacturingTextile industryBatavia and Sarga fabricDefect detectionImage analysisArtificial visionQuality inspectionInteligencia artificialIndustria textilArtificial intelligenceTextile industryArtículo de datosThis dataset, collected during November 2022 at Textil Santanderina, a leading textile manufacturer based in Cabezón de la Sal (Cantabria, Spain), comprises high-resolution images of Batavia and Sarga fabrics. The images were captured as part of a project to document and analyze the intricate weaves and patterns of these fabrics. Using a high-resolution camera under controlled lighting conditions, detailed images were obtained to ensure consistent quality and accurate representation of the fabric's texture and colour. The dataset is provided in processed format, where images have been downscaled from 16 bits to 8 bits, cropped, and classified into cases and controls. The primary reuse potential of this dataset lies in its application for Artificial Intelligence (AI) and Machine Learning (ML) models aimed at defect detection in textile manufacturing. By leveraging these high-quality processed images, researchers and developers can train models to identify and classify various types of fabric defects, such as weave inconsistencies, colour variations, and surface irregularities. This can significantly enhance the efficiency and accuracy of quality control processes in textile production. Additionally, the dataset serves as a valuable resource for academic research in textile engineering and material science. It can be used to study the properties and behaviours of Batavia and Sarga weaves under different conditions, contributing to advancements in fabric design and manufacturing techniques. The detailed visual information provided by the processed images also supports the development of new methodologies for automated textile inspection and quality assurance. By making this dataset available, Textil Santanderina and University of Burgos aim to support innovation and improvement in textile quality control through AI-driven solutions, fostering collaboration and development within the industry.The funding for this project was provided by the DECENT (Deep Learning for automatic Textile Inspection) initiative under the DIH-World 2nd Open Call framework. The authors express their gratitude to INADE for their collaboration in acquiring the images.Elsevier202520252025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/10259/10545reponame:Repositorio Institucional de la Universidad de Burgos (RIUBU)instname:Universidad de Burgos (UBU)InglésData in Brief. 2025, V. 59, 111451https://doi.org/10.1016/j.dib.2025.111451Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:riubu.ubu.es:10259/105452026-05-28T07:56:11Z
dc.title.none.fl_str_mv Dataset for defect detection in textile manufacturing
title Dataset for defect detection in textile manufacturing
spellingShingle Dataset for defect detection in textile manufacturing
Gil Arroyo, Beatriz
Textile manufacturing
Textile industry
Batavia and Sarga fabric
Defect detection
Image analysis
Artificial vision
Quality inspection
Inteligencia artificial
Industria textil
Artificial intelligence
Textile industry
title_short Dataset for defect detection in textile manufacturing
title_full Dataset for defect detection in textile manufacturing
title_fullStr Dataset for defect detection in textile manufacturing
title_full_unstemmed Dataset for defect detection in textile manufacturing
title_sort Dataset for defect detection in textile manufacturing
dc.creator.none.fl_str_mv Gil Arroyo, Beatriz
Marcos Sanz, Juan
Arroyo Puente, Ángel
Urda Muñoz, Daniel
Basurto Hornillos, Nuño
Herrero Cosío, Álvaro
author Gil Arroyo, Beatriz
author_facet Gil Arroyo, Beatriz
Marcos Sanz, Juan
Arroyo Puente, Ángel
Urda Muñoz, Daniel
Basurto Hornillos, Nuño
Herrero Cosío, Álvaro
author_role author
author2 Marcos Sanz, Juan
Arroyo Puente, Ángel
Urda Muñoz, Daniel
Basurto Hornillos, Nuño
Herrero Cosío, Álvaro
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Textile manufacturing
Textile industry
Batavia and Sarga fabric
Defect detection
Image analysis
Artificial vision
Quality inspection
Inteligencia artificial
Industria textil
Artificial intelligence
Textile industry
topic Textile manufacturing
Textile industry
Batavia and Sarga fabric
Defect detection
Image analysis
Artificial vision
Quality inspection
Inteligencia artificial
Industria textil
Artificial intelligence
Textile industry
description Artículo de datos
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/10259/10545
url https://hdl.handle.net/10259/10545
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Data in Brief. 2025, V. 59, 111451
https://doi.org/10.1016/j.dib.2025.111451
dc.rights.none.fl_str_mv Atribución-NoComercial 4.0 Internacional
http://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositorio Institucional de la Universidad de Burgos (RIUBU)
instname:Universidad de Burgos (UBU)
instname_str Universidad de Burgos (UBU)
reponame_str Repositorio Institucional de la Universidad de Burgos (RIUBU)
collection Repositorio Institucional de la Universidad de Burgos (RIUBU)
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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