A suitable neural network to detect textile defects

Keywords

• scratch detection
• fabric defect detection
• local thresholding
• fabric inspection
• multilayer neural networks
• garment quality control
• defect feature extraction
• hole detection
• binarization
• low-cost inspection system

CCDS Authors

Prof. M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

• Founder Director, CCDS
• Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

References

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Cited By

1. 1.Yiting Li, Haisong Huang, Qingsheng Xie, Liguo Yao, Qipeng Chen. (2018). Research on a Surface Defect Detection Algorithm Based on MobileNet-SSD. Applied Sciences, 8(9), 1678[10.3390/app8091678]
2. 2.Md. Tarek Habib, M. Rokonuzzaman. (2011). Distinguishing Feature Selection for Fabric Defect Classification Using Neural Network. Journal of Multimedia, 6(5)[10.4304/jmm.6.5.416-424]
3. 3.Tanjim Mahmud, Juel Sikder, Rana Jyoti Chakma, Jannat Fardoush. (2021). Fabric Defect Detection System. Advances in intelligent systems and computing, 788–800[10.1007/978-3-030-68154-8_68]
4. 4.Md. Tarek Habib, Shaon Bhatta Shuvo, Mohammad Shorif Uddin, Farruk Ahmed. (2016). Automated textile defect classification by Bayesian classifier based on statistical features. , 101–105[10.1109/iwci.2016.7860347]
5. 5.Savvas Vassiliadis, Maria Rangoussi, Ahmet Cay, Christopher Provatidis. (2010). Artificial Neural Networks and Their Applications in the Engineering of Fabrics. Sciyo eBooks[10.5772/10475]
6. 6.Habib, Tarek. (2026). Automated Fabric Defect Inspection: A Survey of Classifiers. Zenodo (CERN European Organization for Nuclear Research)[10.5281/zenodo.21806590]
7. 7.Dirk Siegmund, Timotheos Samartzidis, Biying Fu, Andreas Braun, Arjan Kuijper. (2017). Fiber Defect Detection of Inhomogeneous Voluminous Textiles. Lecture notes in computer science, 278–287[10.1007/978-3-319-59226-8_27]
8. 8.Md. Tarek Habib, M. Rokonuzzaman. (2012). A Set of Geometric Features for Neural Network-Based Textile Defect Classification. ISRN Artificial Intelligence, 2012, 1–16[10.5402/2012/643473]
9. 9.Md. Mozaharul Mottalib, M. Rokonuzzaman, Md. Tarek Habib, Farruk Ahmed. (2015). Fabric defect classification with geometric features using Bayesian classifier. , 137–140[10.1109/icaee.2015.7506815]
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