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Automated Quality Inspection of Microfluidic Chips Using Morphologic Techniques

  • Thomas Schwarzbauer
  • Martin Welk
  • Chris Mayrhofer
  • Rainer Schubert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7883)

Abstract

We apply morphological image processing for quality inspection of microfluidic chips. Based on a comparison of measured topographies with design data, we provide a coherent solution to four central tasks in the quality assessment of injection moulded polymer devices: determination of channel depth, identification of burrs, calculation of transcription accuracy, and detection of defective regions. Experimental comparison to manual quality inspection procedures demonstrates the good performance of the proposed automated method, and reveals its clear advantages in terms of objectivity and reliability.

Keywords

Defect Detection Image Registration Image Processing Technique Channel Depth Quality Inspection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Thomas Schwarzbauer
    • 1
    • 2
  • Martin Welk
    • 2
  • Chris Mayrhofer
    • 1
  • Rainer Schubert
    • 2
  1. 1.Sony DADC AustriaAnif/SalzburgAustria
  2. 2.University for Health Sciences, Medical Informatics and Technology (UMIT)Hall/TyrolAustria

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