Research Of Print Defects Recognition System Based On Machine Vision

Machine vision means simulating the human visual function with computers. It can extract information from image of objective things, and the information can be processed and understood. Ultimately it will be used for practical test, measurement, control and identification. With the development of computer, image processing and machine vision technology is probably to identify the print defects with machine vision.Combining with machine vision, image processing, recognition and other technologies in the printing industry, it was studied to print defects recognition system based on machine vision in this paper. Firstly, an experiment system of print defects recognition based on machine vision was designed and set up. The system consists of TMS320DM642, area array CCD cameras, monitors, lighting, simulated print station and the acquisition synchronized control device (rotary encoder) etc. The system provided a platform for the research of print defects on-line identification. Secondly, the collected images were analyzed and the image pre-processing process, including graying, filtering, enhancement, edge extraction and edge difference, was put forward. Thirdly, the defect recognition algorithm was studied and was chose to the BP neural network algorithm to achieve the classification of defects. Finally, using CCS2.0 as the platform, the software of print defect identification system with C, C++ language was developed. The software can achieve the functions of image acquisition, image pre-processing, image recognition, image display and so on.The print defects recognition system basically meets the real-time requirements, and it is easy to operate. But there are many aspects to be improved in order to satisfy actual application. At last, some notions of improvements have been given.