Unsupervised surface defect detection using deep autoencoders and data augmentation

• Main Authors: Abdul Mujeeb, Dai, Wenting, Erdt, Marius, Sourin, Alexei
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Computer science and engineering; Defect Detection; Automatic Optical Inspection
• Online Access: https://hdl.handle.net/10356/137972
• Institution: Nanyang Technological University

Surface level defect detection, such as detecting missing components, misalignments and physical damages, is an important step in any manufacturing process. In this paper, similarity matching techniques for manufacturing defect detection are discussed. We are proposing an algorithm which detects sur...