What we check

DEFECTS & ANOMALIES

Fast and reliable machine vision methods

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.

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Machine vision methods, testing, structures, surfaces, chip detection, pores

microfluidic structures

  • Detection of particles, hair, scratches, bubbles
Machine vision methods, testing, structures, surfaces, chip detection, pores

Surface inspection

  • Scratch detection
  • deformations
Machine vision methods, testing, structures, surfaces, chip detection, pores

Pores & burrs Metal component

  • detection of pores
  • Burr detection
Machine vision methods, testing, structures, surfaces, chip detection, pores

pipe chip detection

  • Detection of chips
  • location
Machine vision methods, testing, structures, surfaces, chip detection, pores

Defects in textiles

  • Anomaly detection in textiles
  • Determination of defect size
Machine vision methods, testing, structures, surfaces, chip detection, pores

anomalies food

  • Foreign body detection
  • classification
  • location
Machine vision methods, testing, structures, surfaces, chip detection, pores

surface defects metal

  • Defect detection through shape-from-shading
  • location
  • size
Machine vision methods, testing, structures, surfaces, chip detection, pores

Defective abrasives

  • Detection of anomalies on structured surfaces
  • location
  • size
Machine vision methods, testing, structures, surfaces, chip detection, pores

Bottleneck anomalies

  • Search area detection
  • Anomaly detection
  • location