Abstract: This research paper provides an overview of the current state of machine learning in surface defect detection for industrial product quality inspection. The study examines traditional machine vision techniques, as well as the latest advancements in deep learning-based approaches. The paper also highlights common challenges faced in the field and presents potential solutions to these challenges. The study concludes with an overview of datasets used for evaluating industrial surface defect detection methods and a comparison of the latest research. This information serves as a valuable reference for future research and development in this field.
Keywords: Surface defect detection, Industrial product quality inspection, Machine vision techniques, Deep learning, Evaluation datasets.
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DOI:
10.17148/IJARCCE.2023.12334
