Toward Automated Fabric Defect Detection: A Survey of Recent Computer Vision Approaches

Rui Carrilho; Ehsan Yaghoubi; José Lindo; Kailash Hambarde; Hugo Proença

doi:10.3390/electronics13183728

journal article Open Access Sep 20, 2024

Toward Automated Fabric Defect Detection: A Survey of Recent Computer Vision Approaches

Rui Carrilho

Ehsan Yaghoubi

José Lindo Kailash Hambarde

Hugo Proença

Electronics Vol. 13 No. 18 pp. 3728 · MDPI AG

View at Publisher Save 10.3390/electronics13183728

Abstract

Defect detection is a crucial part of the pipeline in many industries. In the textile industry, it is especially important, as it will affect the quality and price of the final product. However, it is mostly performed by human agents, who have been reported to have poor performance, along with requiring a costly and time-consuming training process. As such, methods to automate the process have been increasingly explored throughout the last 20 years. While there are many traditional approaches to this problem, with the advent of deep learning, machine learning-based approaches now constitute the majority of all possible approaches. Other articles have explored traditional approaches and machine learning approaches in a more general way, detailing their evolution over time. In this review, we summarize the most important advancements in the last 5 years and focus mostly on machine learning-based approaches. We also outline the most promising avenues of research in the future.

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Details

Published: Sep 20, 2024
Vol/Issue: 13(18)
Pages: 3728
License: View

Authors

R

Rui Carrilho

IT: Instituto de Telecomunicações, University of Beira Interior, 6201-001 Covilhã, Portugal

E

Ehsan Yaghoubi

Department of Informatics, Universität Hamburg, 20148 Hamburg, Germany

J

José Lindo

Paulo de Oliveira, 6200-275 Covilhã, Portugal

K

Kailash Hambarde

IT: Instituto de Telecomunicações, University of Beira Interior, 6201-001 Covilhã, Portugal

H

Hugo Proença

IT: Instituto de Telecomunicações, University of Beira Interior, 6201-001 Covilhã, Portugal

Funding

FCT/MCTES Award: 2022-C05i0101-02

NextGenerationEU program Award: 2022-C05i0101-02

Cite This Article

Rui Carrilho, Ehsan Yaghoubi, José Lindo, et al. (2024). Toward Automated Fabric Defect Detection: A Survey of Recent Computer Vision Approaches. Electronics, 13(18), 3728. https://doi.org/10.3390/electronics13183728

Toward Automated Fabric Defect Detection: A Survey of Recent Computer Vision Approaches

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