Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 3
944-950

Channel and spatial joint attention based defect detection method in complex texture ceramic tile

Ye Xufang1,2a
Chen Mei1,2a
Li Hui1,2a
Cao Yang2b
Wang Xibin3
1. State Key Laboratory of Public Big Data, Guiyang 550000, China
2. a. School of Computer Science & Technology, b. School of Mechanical Engineering, Guizhou University, Guiyang 550000, China
3. School of Data Science, Guizhou Institute of Technology, Guiyang 550000, China
DOI: 10.19734/j.issn.1001-3695.2023.06.0303

Abstract

In the complex texture of the tile surface, there are more low-visibility small defects, and the interference from the complex textured background is serious. This results high false detection and false alarm rate using traditional object detection methods. To enhance the efficiency of defect detection, this paper proposed a defect detection approach on complex textured tile surfaces based on the joint attention mechanisms of channels and spatial. Firstly, to enhance the feature expression of small defects, it proposed a selective feature fusion method by modeling the relationship between deep and shallow feature channels. Secondly, it designed a joint channel and spatial attention module that selected key feature channels and suppressed texture regions through channel and spatial attention, enabling the model to focus on learning defect features and enhancing its ability to discriminate between defects and texture. Finally, it validated the approach on a dataset of complexly textured ceramic tile surface defects. The experimental results demonstrate that compared to the AFF and CBAM methods, the selective feature fusion method and channel & spatial joint attention achieved improvements of 5.3 AP and 6.32 AP, respectively. In addition, this paper compared the overall approach with the existing tile detection method YOLOv5 and texture fabric defect detection method AFAM. The results show that it outperforms these methods, with respective improvements of 1.32 AP and 2.12 AP.

Foundation Support

国家自然科学基金资助项目(62162010,72161005)
贵州省科技资助项目(黔科合支撑［2021］一般449,黔科合基础-ZK［2022］一般184,黔科合支撑［2022］一般271,黔科合成果［2023］一般010)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.06.0303
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 3
Section: Technology of Graphic & Image
Pages: 944-950
Serial Number: 1001-3695(2024)03-046-0944-07

Publish History

[2023-12-08] Accepted Paper
[2024-03-05] Printed Article

Cite This Article

叶旭芳, 陈梅, 李晖, 等. 基于联合注意力的复杂纹理瓷砖缺陷检测方法 [J]. 计算机应用研究, 2024, 41 (3): 944-950. (Ye Xufang, Chen Mei, Li Hui, et al. Channel and spatial joint attention based defect detection method in complex texture ceramic tile [J]. Application Research of Computers, 2024, 41 (3): 944-950. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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