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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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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. |
format | Online Article Text |
id | pubmed-9325596 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT sunning realtimeimagedefectdetectionsystemofclothdigitalprintingmachine AT caobotao realtimeimagedefectdetectionsystemofclothdigitalprintingmachine |