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Real-Time Image Defect Detection System of Cloth Digital Printing Machine

In order to solve the surface defects such as white silk, spots, and wrinkles on the fabrics in the process of digital printing production, a surface defect detection system for printed fabrics based on the accelerated robust feature algorithm is proposed. The image registration is mainly carried ou...

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Detalles Bibliográficos
Autores principales: Sun, Ning, Cao, Botao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325596/
https://www.ncbi.nlm.nih.gov/pubmed/35909836
http://dx.doi.org/10.1155/2022/5625945
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author Sun, Ning
Cao, Botao
author_facet Sun, Ning
Cao, Botao
author_sort Sun, Ning
collection PubMed
description In order to solve the surface defects such as white silk, spots, and wrinkles on the fabrics in the process of digital printing production, a surface defect detection system for printed fabrics based on the accelerated robust feature algorithm is proposed. The image registration is mainly carried out by the speeded up robust features (SURF) algorithm; the bidirectional unique matching method is used to reduce the mismatch points, realize the accurate registration of the image, and extract the defect information through the difference algorithm. The experiment uses multiple images to verify the performance of the improved SURF algorithm. The experimental results show that the detection accuracy of the new system for surface defects of printed fabrics reaches 98%. The algorithm has higher detection rate and faster detection speed, which can meet the needs of practical industrial applications.
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spelling pubmed-93255962022-07-28 Real-Time Image Defect Detection System of Cloth Digital Printing Machine Sun, Ning Cao, Botao Comput Intell Neurosci Research Article In order to solve the surface defects such as white silk, spots, and wrinkles on the fabrics in the process of digital printing production, a surface defect detection system for printed fabrics based on the accelerated robust feature algorithm is proposed. The image registration is mainly carried out by the speeded up robust features (SURF) algorithm; the bidirectional unique matching method is used to reduce the mismatch points, realize the accurate registration of the image, and extract the defect information through the difference algorithm. The experiment uses multiple images to verify the performance of the improved SURF algorithm. The experimental results show that the detection accuracy of the new system for surface defects of printed fabrics reaches 98%. The algorithm has higher detection rate and faster detection speed, which can meet the needs of practical industrial applications. Hindawi 2022-07-19 /pmc/articles/PMC9325596/ /pubmed/35909836 http://dx.doi.org/10.1155/2022/5625945 Text en Copyright © 2022 Ning Sun and Botao Cao. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Sun, Ning
Cao, Botao
Real-Time Image Defect Detection System of Cloth Digital Printing Machine
title Real-Time Image Defect Detection System of Cloth Digital Printing Machine
title_full Real-Time Image Defect Detection System of Cloth Digital Printing Machine
title_fullStr Real-Time Image Defect Detection System of Cloth Digital Printing Machine
title_full_unstemmed Real-Time Image Defect Detection System of Cloth Digital Printing Machine
title_short Real-Time Image Defect Detection System of Cloth Digital Printing Machine
title_sort real-time image defect detection system of cloth digital printing machine
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325596/
https://www.ncbi.nlm.nih.gov/pubmed/35909836
http://dx.doi.org/10.1155/2022/5625945
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