Automation of Steel Drums Visual Inspection Using Deep Learning and Image Recognition

Abstract

In this paper, we propose a technology for diagnosing the state of objects for automated inspection of facility infrastructure. As part of efforts to link and integrate non-destructive inspection data, we automatically estimate the deterioration state of steel drums that store waste based on image recognition. Specifically, the area and type of rust on the steel drums surface are automatically estimated by using semantic segmentation.