MABRI.VISION uses a variety of methods to detect defects and anomalies in products and materials. By using image processing algorithms it is possible to detect defects such as cracks, holes, pores, burrs or deformations in products or materials. The use of 3D sensors can also help to detect defects that cannot be detected with 2D imaging.

The use of machine learning methods, such as the use of neural networks , is another way of detecting defects and anomalies. These methods can be trained to detect defects and anomalies based on pattern recognition and pattern matching. The use of deep learning technologies can also help to improve the detection of defects and anomalies.