Difference between revisions of "Publications:Intelligent Monitoring of the Offset Printing Process"
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| − | |Name=Bergman, Lars | + | |Name=Bergman, Lars (lb) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Intelligenta system (IS-lab) (3941));Verikas, Antanas (av) (0000-0003-2185-8973) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Intelligenta system (IS-lab) (3941)) |
|Title=Intelligent Monitoring of the Offset Printing Process | |Title=Intelligent Monitoring of the Offset Printing Process | ||
|PublicationType=Conference Paper | |PublicationType=Conference Paper | ||
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|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:556064}} | |diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:556064}} | ||
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Latest revision as of 21:42, 30 September 2016
Property "Author" has a restricted application area and cannot be used as annotation property by a user. Property "Author" has a restricted application area and cannot be used as annotation property by a user.
| Title | Intelligent Monitoring of the Offset Printing Process |
|---|---|
| Author | |
| Year | 2004 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | Proceedings of the IASTED International Conference on Neural Networks and Computational Intelligence |
| Conference | International Conference on Neural Networks and Computational Intelligence, Grindelwald, 23 - 25 February 2004 |
| DOI | |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:556064 |
| Abstract | In this paper, we present a neural networks and image analysis based approach to assessing colour deviations in an offset printing process from direct measurements on halftone multicoloured pictures--there are no measuring areas printed solely to assess the deviations. A committee of neural networks is trained to assess the ink proportions in a small image area. From only one measurement the trained committee is capable of estimating the actual amount of printing inks dispersed on paper in the measuring area. To match the measured image area of the printed picture with the corresponding area of the original image, when comparing the actual ink proportions with the targeted ones, properties of the 2-D Fourier transform are exploited. |