Abstract

Six approaches in X-ray testing for automated defect recognition were discussed. In the first method, neural networks were used for selection of the regions of interest (ROI) and configuration of the detection filters. Another method based on the signal synchronised filter was examined for automatic defect recognition in aluminium castings. The other four methods discussed were the block correlative approach; defect recognition using shape features; defect recognition using linear classifiers and inspection of moving pieces.