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Tactile-Based Fabric Defect Detection Using Convolutional Neural Network With Attention Mechanism

文献类型：期刊论文

作者Bin Fang2; Long, Xingming3; Sun, Fuchun2; Liu, Huaping2; Zhang, Shixin4; Fang, Cheng1
刊名IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
出版日期2022
卷号71页码:9
ISSN号0018-9456
关键词Fabrics Feature extraction Frequency-domain analysis Tactile sensors Cameras Visualization Sensors Attention mechanism defect detection vision-based tactile sensor
DOI10.1109/TIM.2022.3165254
英文摘要This article proposes a fabric structure defect detection method based on the vision-based tactile sensor. The result will be robust by using the tactile sensor regardless of dyeing patterns which can influence the result if some other sensors are used, e.g., vision perception. It also reduces the influence of ambient light on defect detection. Therefore, the proposed method can be more robust and universal than conventional visual methods. A robotic arm equipped with the tactile sensors was used to automate and standardize the data collection process and construct fabric datasets. In addition, a convolutional neural network (CNN) integrated with attention mechanism in the channel domain was developed to detect fabric types. The proposed network employed frequency domain filtering to remove or weaken the influence of normal fabric texture information to improve defect detection efficiency and accuracy. Finally, several experiments were conducted to demonstrate the proposed method's superiority to a visual defect detection method for detecting structural defects. In addition, the efficiency of the proposed method is evaluated. Experimental results show that the proposed method is feasible and efficient to meet the real-world detection requirements.
资助项目National Natural Science Foundation of China[62173197] ; Beijing Science Technology Project[Z191100008019008]
WOS研究方向Engineering ; Instruments & Instrumentation
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000795104800001
源URL[http://119.78.100.204/handle/2XEOYT63/19562]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Sun, Fuchun
作者单位1.Univ Southern Denmark, Maersk McKinney Moller Inst, DK-5230 Odense, Denmark
2.Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol, Inst Artificial Intelligence, State Key Lab Intelligent Technol & Syst,Dept Com, Beijing 100084, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Beijing 100086, Peoples R China
4.China Univ Geosci Beijing, Sch Engn & Technol, Beijing 100083, Peoples R China
推荐引用方式
GB/T 7714		 Bin Fang,Long, Xingming,Sun, Fuchun,et al. Tactile-Based Fabric Defect Detection Using Convolutional Neural Network With Attention Mechanism[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2022,71:9.
APA Bin Fang,Long, Xingming,Sun, Fuchun,Liu, Huaping,Zhang, Shixin,&Fang, Cheng.(2022).Tactile-Based Fabric Defect Detection Using Convolutional Neural Network With Attention Mechanism.IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,71,9.
MLA Bin Fang,et al."Tactile-Based Fabric Defect Detection Using Convolutional Neural Network With Attention Mechanism".IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 71(2022):9.

入库方式： OAI收割

来源：计算技术研究所

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