Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY

Tamás Czimmermann, Gastone Ciuti, Mario Milazzo, Marcello Chiurazzi, Stefano Roccella, Calogero Maria Oddo, Paolo Dario
2020 Sensors  
This paper reviews automated visual-based defect detection approaches applicable to various materials, such as metals, ceramics and textiles. In the first part of the paper, we present a general taxonomy of the different defects that fall in two classes: visible (e.g., scratches, shape error, etc.) and palpable (e.g., crack, bump, etc.) defects. Then, we describe artificial visual processing techniques that are aimed at understanding of the captured scenery in a mathematical/logical way. We
more » ... inue with a survey of textural defect detection based on statistical, structural and other approaches. Finally, we report the state of the art for approaching the detection and classification of defects through supervised and non-supervised classifiers and deep learning.
doi:10.3390/s20051459 pmid:32155900 fatcat:rsdnszztffbadllniclol3pjvi