The accuracy of overprint is one of the essential factors for the qualities of modern color printing technology. Using machine vision technology and image processing technology to detect overprint quality can steadily and accurately monitor overprint quality and avoid the disadvantages of human eyes detection. This paper firstly introduces the gradient entropy and direction constraint into sequential similarity detection algorithm (SSDA); then a novel joint function is proposed as similarity measure function; finally, Powell optimization algorithm is adopted to optimize the registration parameters. Simulation results, in both qualitative and quantitative, show that our proposed algorithm noticeably reduces the registration error compared with the traditional method. The obtained accurate registration parameter would make it possible for identifying the overprint qualities, sending signal when the misregister and deviation adjusting signal occur. In brief, our proposed algorithm can make the printing machine automatically adjust the plate location and correct the standard deviation in color printing system.
Image registration Overprint Color printing system Measurement entropy Sequential similarity detection Similarity measure
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