Object detection for dynamic adaptation of interconnections in inkjet printed electronics

A computer vision system for automatic detection of interconnection points in inkjet printed interconnected electronics modules during the manufacturing process is described. The location data can be used for calculating the amount of misalignments and the required corrections. The method uses a local filtering operation for finding candidate regions, from which the false matches are filtered out by classification using an artificial neural network. Experiments show that atypical false match rate is as low as 0.18%. The location data is later used for correcting the wiring that is inkjetted on top of the layout to connect the connectors correctly.