An Image-Based Method for Objectively Assessing Injection Moulded Plastic Quality

  • Morten Hannemose
  • Jannik Boll Nielsen
  • László Zsíros
  • Henrik Aanæs
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10270)


In high volume productions based on casting processes, like high-pressure die casting (HPDC) or injection moulding, there is a wide range of variables that affect the end quality of produced parts. These variables include production parameters (temperature, pressure, mixture), and external factors (humidity, temperature, etc.). With this many variables it is a challenge to maintain a stable output quality, wherefore massive amounts of resources are spent on quality assurance (QA) of produced parts. Currently, this QA is done manually through visual inspection. We demonstrate how a multispectral imaging system can be used to automatically rate the quality of a produced part using an autocorrelation and a Fourier-based method. These methods are compared with human rankings and achieve good correlations on a variety of samples.


Quality inspection Plastics Injection moulding Maximum autocorrelation factor Multispectral Fourier transform 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Morten Hannemose
    • 1
  • Jannik Boll Nielsen
    • 1
  • László Zsíros
    • 2
  • Henrik Aanæs
    • 1
  1. 1.DTU ComputeTechnical University of DenmarkKongens LyngbyDenmark
  2. 2.Department of Polymer EngineeringBudapest University of Technology and EconomicsBudapestHungary

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