Fabric Defect Detection Using Competitive Cat Swarm Optimizer Based RideNN and Deep Neuro Fuzzy Network

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Maheshwari S. Biradar ◽  
Basavaprabhu G. Sheeparamatti ◽  
Pradeep Mitharam Patil
Keyword(s):  
Defect Detection ◽  
Fabric Defect Detection ◽  
Neuro Fuzzy ◽  
Fabric Defect ◽  
Fuzzy Network

Fabric defect detection based on adaptive LBP and SVM

2010 ◽  
Vol 30 (6) ◽  
pp. 1597-1601 ◽  
Author(s):  
Rong FU ◽  
Mei-hong SHI
Keyword(s):  
Defect Detection ◽  
Fabric Defect Detection ◽  
Fabric Defect

Machine Vision Window Division on Self-Adaptation

2011 ◽  
Vol 460-461 ◽  
pp. 617-620
Author(s):  
Xiu Chen Wang
Keyword(s):  
Image Analysis ◽  
Machine Vision ◽  
Defect Detection ◽  
Actual Situation ◽  
Adaptive Window ◽  
Fabric Defect Detection ◽  
Fabric Defect ◽  
Self Adaptation ◽  
Recognition Efficiency ◽  
Division Model

Aiming at time-consuming and ineffective problem of image window division in fabric defect detection, this paper proposes a new adaptive division method after a large number of experiments. This method can quickly and exactly recognize defect feature. Firstly, a division model on adaptive window is established, secondly, the formula to anticipate generally situation of fabric image is given according to the peaks and valleys change in the model, and methods to calculate the division size and position of adaptive window are given. Finally, we conclude that the algorithm in this paper can quickly and simply select the size and position of window division according to actual situation of different fabric images, and the time of image analysis is shortened and the recognition efficiency is improved.

A Novel Fabric Defect Detection Network Based on Attention Mechanism and Multi-Task Fusion

2021 ◽  
Author(s):  
Zhengrui Peng ◽  
Xinyi Gong ◽  
Zhenfeng Lu ◽  
Xiangyi Xu ◽  
Bengang Wei ◽  
...  
Keyword(s):  
Defect Detection ◽  
Attention Mechanism ◽  
Fabric Defect Detection ◽  
Fabric Defect
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