ARGUS: A system for inspecting colour printing quality

Caj Södergård, Juuso Äikäs

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review


    The use of machine vision technology is being investigated at VTT for improving the color quality and productivity of web offset printing. The visual inspection of color quality is performed by a traversing color CCD camera which images the moving web under a stroboscopic light. The measuring locations and goal values for the color register, the ink density, and the gray balance are automatically determined from the postscript description of the digital page. A set of criteria is used to find the best-suited spots for the measurements. In addition to providing data for the on-line control, the page analysis estimates the zone wise ink consumption of the printing plates as a basis for presetting the ink feed. Target colorimetric CIE-values for gray balance and critical colors are determined from the image originals. The on-line measurement results and their deviations from the target values are displayed in an integrated manner. The paper gives test results of computation times, register error measuring with and without test targets and the color measuring capabilities of the system. The results show that machine vision can be used in the on-line inspection of the color print quality.
    Original languageEnglish
    Title of host publicationIntelligent Robots and Computer Vision XIII
    Subtitle of host publicationAlgorithms and Computer Vision; (1994)
    PublisherInternational Society for Optics and Photonics SPIE
    Pages513 - 521
    ISBN (Print)0-8194-1688-6
    Publication statusPublished - 1994
    MoE publication typeA4 Article in a conference publication
    EventIntelligent Robots and Computer Vision XIII; Algorithms and Computer Vision - Boston, United States
    Duration: 31 Oct 19942 Nov 1994

    Publication series

    SeriesProceedings of SPIE


    ConferenceIntelligent Robots and Computer Vision XIII; Algorithms and Computer Vision
    Country/TerritoryUnited States


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