Vision Detection and System Integration 

Specific solutions to your needs for laboratory, production and quality control applications. From the conception
to the production.

Our offer:

  • simple inspections, manually or with robot systems
  • fully automated inspection systems
    (e.g. automatic robot systems for various tasks like loading and sorting)
  • fully automated physical test stations
  • Step-by-step monitoring by computer-aided image recognition systems, which can, at any time, correctly interene in the process






By applying appearancebased methods automatic product identification and classification can be performed. Non-expected changes in product or batch appearance will be detected. Furthermore, with deep learning based approaches normal changes in products or batch appearance and environmental variability can be suppressed; therefore, only the defect product with non-expected behavior will be detected. These deep learning based software frameworks are algorithms in machine learning which allow to vision detect otherwise impossible inspection and classification challenges. This makes vision detection suitable for a whole new area of applications in production, packaging, laboratory, and quality departments.






Detection of missing or wrong objects in delivery trays




Detection of RFID within injection molded  products




Inspection of glue line on product against   missing glue






Advanced vision detection systems allow not only to detect features on samples or products but also allow to measure them. This includes measuring of: Liquid heights in containers, overall dimensions of parts or features, distances between features, circularity of holes, straightness of edges, angles between features, and many other measurements. By use of several camera systems also features and distances between different images from different cameras on large products can be measured without getting the product moved. Furthermore, automatic reading of numbers, letters, and barcodes by the vision detection system will allow to check for correct labeling of products or samples.















Detection of
objects in samples
and measuring of
fill levels



of diameters,
circularity, and



Counting of
objects and


Recognition of
numbers, letters,
and barcodes










 Aestethic inspection

Aesthetic inspection includes the detection of defects on surfaces regarding surface structure as well as printing or engraving on surfaces.
Surfaces of products or samples come in many different types made from different materials and produced in different processes. This results in wanted and unwanted surface structures. Wanted surface structures such as grinded surfaces or brushed surfaces for decoration are surface variabilities which have to be suppressed during the vision detection process by use of deep learning based approaches or similar methods. After suppressing such wanted surface structures the unwanted surface defects such as scratches, holes, or stains can be detected.

Printed or engraved surfaces often include letters, numbers, or symbols. Those letters, numbers or symbols might still be readable but form quality aspect they do not reflect the high quality of a product. Therefore, by use of deep learning based approaches such deviations from wanted printings can be detected and appropriate measures can be taken. 





Detection of 
scratches and
other anomalies
on a surface.




Detection of stains
or changes in