Quality control and inspection

Presence and correctness check

Quality control is performed by analyzing the image using the following functions:

  • Colour analysis – checking for the presence of a colour spectrum, this function is used in the case of different coloured surfaces which allows the presence of components in a given location to be determined in a robust way.
  • Shape check – By recognizing the shape of objects and comparing it to a reference, it allows checking for the presence of the correct shape at the inspection site.
  • Barcode, QR and OCR – Recognition of numbers and text after engraving or printing on the product and reading barcodes and QR codes and checking or automatically categorizing them.
  • Change – Intelligent analysis to recognize change in the inspection region easily used to recognize only the presence of objects such as hand and tool or components.
  • Flags – The analytically learned shape search function in the image allows you to quickly and easily define the object of interest for inspection.

Inspection of quality and shapes

Detailed shape analysis can be used to determine the size, angle and relative distance to references, which allows precise evaluation of the correctness of the objects.

Neural networks for quality control

A modern and advanced form of image analysis using artificial intelligence. The creation of functionality takes the form of learning from real images focused on objects, components and parts and in this way can be learned and continuously refined. Over time, inspection thus becomes a robust function that recognizes object shapes as well as defects on objects with high accuracy, even under changing ambient or process conditions. It is this adaptability that elevates this type of inspection above classical image analysis methods.

Neural Networks for Quality Inspection

Defect detection on objects and surfaces is an essential part of a modern inspection workplace. Using the learned defects, the system can recognize material defects or surface and design defects.

Object position recognition

Object detection using CAD

An essential part of a vision system is the recognition of the position of objects in space and the automatic adaptation of the production technology to the new position, e.g. visual guidance, camera system, robotic arm and others…

The ability to recognize the position using CAD files, DXF curves and STL models. In this way it is possible to link technical drawings with the camera program.

Object detection using detection tags

A more robust method of position detection using detection marks suitable for dynamically changing positions of objects, tools and more.

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