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Imperfection recognition on lenses


A company manufactures high-quality articles for the cosmetics industry. Specifically, it manufactures a plastic lens to optically enhance a cream container.

  • Goals: 
    • Only objects of the highest quality are used: Without scratches, contaminations, inclusions etc.  
    • Quality inspections should be automated (despite imperfections being difficult for the human eye to detect)
  • Challenge: 
    • Process differences of training vs. test data (lighting, background)



Image recognition by Deep Neural Networks:

  • Installation of a camera and collection of image data
  • Labeling images of defective products (manually)
  • Training a deep neural network
  • Implementation and integration of the quality assurance into the running production



  • Automation of manual, less “attractive” activities
  • Increasing the quality of finished products

Your contact

Dragan Sunjka msg

Dragan Sunjka
Lead IT Consultant
Automotive & Manufacturing