Automated Quality Inspection of Microfluidic Chips Using Morphologic Techniques

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.