The work aims to propose a set of printing defects detection algorithms applied in the actually disturbing industrial environment, so as to solve the problem that some traditional printing defects detection algorithms are incompetent in detecting speed and accuracy, etc. due to such influencing factors as interferences of dust and vibration of transmitter. The algorithms were mainly composed of image preprocessing, template fabrication, template matching, dust treatment and defects extraction. Wherein, image preprocessing mainly included image denoising, image rotation, image edge normalizing, image cutting, image translation and other links. The running results of such algorithms in the actual industrial assembly line showed that, if the 400 mm × 400 mm printing matters were detected, the fastest detection speed could be less than 1 s and the detection accuracy could reach 0.1 mm. In conclusion, the proposed algorithms can add image edge normalizing to traditional preprocessing, carry out morphological processing on the frame difference result diagram of printing matters, and overcome the interferences caused by dust and vibration of transmitter, etc. in the industrial environment.