Detecting a defective nozzle in a digital printing system

A system for detecting a defective part (DP) in a digital printing system (DPS), the system comprising:

• an interface, which is configured to receive:
• (i) a first digital image (FDI) to be printed by the DPS, and (ii) a second digital image (SDI) acquired from a printed image produced by the DPS;
• and
• a processor, wherein
• in a training phase, the processor is configured, to:
• (i) produce, for one or more first selected regions in the FDI, a first set of one or more synthetic images having a defect caused by the DP in the one or more first selected regions, (ii) select, based on a predefined selection criterion, the first selected regions that comprise features for training a neural network (NN), and (iii) train the NN to detect the defect using at least one of the synthetic images of the first set;
• and
• in a detection phase that is subsequent to the training phase, the processor is configured, to:
• (i) apply the trained NN for identifying, in the SDI, one or more second regions suspected of having the defect, (ii) produce, for each of the second regions, a second set of one or more synthetic images having one or more DPs producing respectively one or more of the defects, and (iii) identify at least the DP by comparing, in each of the second regions, between the SDI and the one or more synthetic images of the second set.