Fabric Defect Classification Algorithm Based on Multi-Scale Feature Fusion of Spatial Attention

Zhiyong Song; Haipeng Pan

doi:10.3788/LOP202259.1010005

[1] Kaynar O, Işik Y E, Görmez Y et al. Fabric defect detection with LBP-GLMC[C], 17333828(2017).

[2] Hu J J, He Z Y, Weng G R et al. Detection of chemical fabric defects on the basis of morphological processing[J]. The Journal of the Textile Institute, 107, 233-241(2016).

[3] Jing J F, Chen S, Li P. Automatic defect detection of patterned fabric via combining the optimal Gabor filter and golden image subtraction[J]. Journal of Fiber Bioengineering and Informatics, 8, 229-239(2018).

[4] Harinath D, Babu K R, Satyanarayana P et al. Defect detection in fabric using wavelet transform and genetic algorithm[J]. Transactions on Machine Learning and Artificial Intelligence, 3, 10(2015).

[5] Zhang Y, Jiang G M, Yao J Z et al. Intelligent segmentation of jacquard warp-knitted fabric using a multiresolution Markov random field with adaptive weighting in the wavelet domain[J]. Textile Research Journal, 84, 28-39(2014).

[6] Li M, Cui S Q, Xie Z P. Application of Gaussian mixture model on defect detection of print fabric[J]. Journal of Textile Research, 36, 94-98(2015).

[7] Jia L, Chen C, Liang J Z et al. Fabric defect inspection based on lattice segmentation and Gabor filtering[J]. Neurocomputing, 238, 84-102(2017).

[8] Qu T, Zou L, Zhang Q L et al. Defect detection on the fabric with complex texture via dual-scale over-complete dictionary[J]. The Journal of the Textile Institute, 107, 743-756(2016).

[9] Tsang C S C, Ngan H Y T, Pang G K H. Fabric inspection based on the Elo rating method[J]. Pattern Recognition, 51, 378-394(2016).

[10] Zhao Z Y, Ye L, Sang H S et al. Application of deep learning in fabric defect detection[J]. Foreign Electronic Measurement Technology, 38, 110-116(2019).

[11] Su Z B, Gao M, Li P F et al. Digital printing defect classification algorithm based on convolutional neural network[J]. Laser & Optoelectronics Progress, 57, 241011(2020).

[12] Zhou J, Jing J F, Zhang H H et al. Real-time fabric defect detection algorithm based on S-YOLOV3 model[J]. Laser & Optoelectronics Progress, 57, 161001(2020).

[13] Anh N T H, Giao B C. An empirical study on fabric defect classification using deep network models[M]. Dang T K, Küng J, Takizawa M, et al. Future data and security engineering, 11814, 739-746(2019).

[14] Gao C, Zhou J, Wong W K et al. Woven fabric defect detection based on convolutional neural network for binary classification[M]. Wong W K. Artificial intelligence on fashion and textiles, 849, 307-313(2018).

[15] Jeyaraj P R, Nadar E R S. Computer vision for automatic detection and classification of fabric defect employing deep learning algorithm[J]. International Journal of Clothing Science and Technology, 31, 510-521(2019).

[16] Das S, Wahi A, Sundaramurthy S et al. Classification of knitted fabric defect detection using artificial neural networks[C], 19575238(2019).

[17] Jing J F, Ma H, Zhang H H. Automatic fabric defect detection using a deep convolutional neural network[J]. Coloration Technology, 135, 213-223(2019).

[18] Shi T T. Deep convolutional neural network fabric defect detection based on Fisher criterion[J]. Computer Systems & Applications, 28, 140-145(2019).

[19] Fu Y J, Zhang H L. Forest fire detection method based on transfer learning of convolutional neural network[J]. Laser & Optoelectronics Progress, 57, 041010(2020).

[20] Yu F, Koltun V. Multi-scale context aggregation by dilated convolutions[EB/OL]. http://arxiv.org/abs/1511.07122

[21] Zhou B L, Khosla A, Lapedriza A et al. Learning deep features for discriminative localization[C], 2921-2929(2016).