KI-PhotoLine – Photogrammetric 2D/3D inspection system using neural networks for in-line anomaly detection

As part of the joint research project »KI-PhotoLine«, a novel approach for fast optical inline quality control is being investigated. This involves the use of an intelligent global 2D defect detection system in combination with a local one-shot 3D defect measurement system.

© Botspot
Concept of the data acquisition system for photogrammetric 3D reconstruction of local defects.
© Botspot

A production line features many objects which can appear in different shapes, materials and surfaces. The solution to be researched should be able to inspect all these objects and subsequently make a sorting decision based on predefined quality standards.

Particular attention is paid to the inspection of highly reflective, very dark and/or matt components. Automated quality control of such industrial products (e.g. painted car body parts) in the process takt and the requirement to perform a 100 percent inline inspection present major challenges for existing solutions.

Fraunhofer IPK focuses its research on the areas of defect detection and pose estimation using machine learning, as well as defect localization in multi-camera systems, researching assistance systems for process optimization and integrating expert knowledge acquired in this research into the learning systems.

Funding notice

The project KI-PhotoLine »Photogrammetric 2D/3D inspection system using neural networks for in-line anomaly detection« is funded by Investitionsbank Berlin and co-financed by the European Regional Development Fund (ERDF).

Interesting for:

Manufacturing industry in which surface inspection is required, e.g.:

  • vehicle construction
  • metal industry
  • furniture and household appliance manufacturing

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