Saliency-based fabric defect detection network with feature pyramid learning and refinement

Zhoufeng Liu; Bo Tian; Xiao Li; Chunlei Li; Yan Dong

doi:10.1117/12.2680034

27 June 2023 Saliency-based fabric defect detection network with feature pyramid learning and refinement

Zhoufeng Liu, Bo Tian, Xiao Li, Chunlei Li, Yan Dong

Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 127050N (2023) https://doi.org/10.1117/12.2680034
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China

Abstract

Fabric defect detection is an essential step of quality control in the textile manufacturing industry. The fabric image texture and defects are complex and diverse, which result in poor detection results and low efficiency of the traditional fabric defect detection algorithm. Visual saliency model can quickly outstand the salient object from the complex background, and has been proven applicable in fabric defect detection. However, the existing saliency detection models still confront great challenges in boundary refinement and line-shaped defect detection. Therefore, a novel saliency-based fabric defect detection network with feature pyramid learning and refinement module is proposed to powerfully characterize features and refine boundary, in which a scale-correlated feature pyramid module (SCFPM) with cross-level connections is proposed to effectively characterize the multi-scale features from the backbone network. Moreover, an auxiliary refinement module (ARM) is designed to further refine and strengthen the input features. Finally, we incorporated the hand-crafted saliency priors to guide the network to generate the accurate saliency maps. Extensive experiments on the built fabric image datasets demonstrate that our proposed model outperforms most state-of-the-art methods under different evaluation metrics.

Citation Download Citation

Zhoufeng Liu, Bo Tian, Xiao Li, Chunlei Li, and Yan Dong "Saliency-based fabric defect detection network with feature pyramid learning and refinement", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 127050N (27 June 2023); https://doi.org/10.1117/12.2680034

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Defect detection

Image processing

Education and training

Feature extraction

Object detection

Performance modeling

Visualization

Show All Keywords

Keywords/Phrases

Search In:

Publication Years