Computer-Vision-Based Fabric Defect Detection: A Survey

By Ajay Kumar. IEEE transactions on industrial electronics (1982. Print), 2008

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Latent Space Autoregression for Novelty Detection (2018, background): “The awareness of an autonomous system to recognize unknown events enables applications in several domains, ranging from video surveillance [7, 11], to defect detection [19] to medical imaging [35].”
Automated Visual Defect Detection for Flat Steel Surface: A Survey (2020, background): “Recently published surveys gradually pay more attention to specific planar materials like fabric [8] and semiconductor [14].”
Active vision in robotic systems: A survey of recent developments (2011, background): “…(Roy et al. 2004); 9. review of 3D measurement quality metrics by environmental factors (MacKinnon et al. 2008b); 10. review of multimodal sensor planning and integration for wide area surveillance (Abidi et al. 2008); 11. review of computer-vision-based fabric defect detection (Kumar 2008).”
Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY (2020, background): “Based on several research studies in the ﬁeld of visual inspection (e.g., [5]), it is possible to use the best ﬁtting approach for a speciﬁc problem.”
Feature selection for surface defect classification of extruded aluminum profiles (2016, background): “Kumar has surveyed 166 sources for computer vision based defect detection and classification, providing an exhaustive review on the different methods used to approach classification [10].”