Automated Defect Recognition

Castings produced for the automotive industry are considered important components for overall roadworthiness. To ensure the safety of construction, it is necessary to check every part thoroughly using non-destructive testing. X-ray testing rapidly became the accepted way of controlling the quality of die-cast pieces. In our research, we are developing approaches based on Convolutional Neural Network (CNN) for defect detection in castings. In order to train the CNN model, a large dataset is necessary. We build the dataset by using synthetic defects. They are simulated using 3D ellipsoidal models and Generative Adversarial Networks (GAN).

Computer Vision for Fault Detection in Aluminum Castings. Mery, D. Encyclopedia of Aluminum and Its Alloys, CRC Press, 2018.

Automatic Defect Recognition in X-ray Testing using Computer Vision. Mery, D.; and Arteta, C. IEEE Winter Conference on Applications of Computer Vision (WACV2017).