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Estimating the amount of cyan, magenta, yellow, and black inks in arbitrary colour pictures
Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID-id: 0000-0003-2185-8973
Department of Applied Electronics, Kaunas University of Technology, Studentu 50, 51368 Kaunas, Lithuania.
Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligenta system (IS-lab).
2007 (engelsk)Inngår i: Neural computing & applications (Print), ISSN 0941-0643, E-ISSN 1433-3058, Vol. 16, nr 2, s. 187-195Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This paper is concerned with the offset lithographic colour printing. To obtain high quality colour prints, given proportions of cyan (C), magenta (M), yellow (Y), and black (K) inks (four primary inks used in the printing process) should be accurately maintained in any area of the printed picture. To accomplish the task, the press operator needs to measure the printed result for assessing the proportions and use the measurement results to reduce the colour deviations. Specially designed colour bars are usually printed to enable the measurements. This paper presents an approach to estimate the proportions directly in colour pictures without using any dedicated areas. The proportions—the average amount of C, M, Y, and K inks in the area of interest—are estimated from the CCD colour camera RGB (L*a*b*) values recorded from that area. The local kernel ridge regression and the support vector regression are combined for obtaining the desired mapping L*a*b* ⇒ CMYK, which can be multi-valued.

sted, utgiver, år, opplag, sider
London: Springer London, 2007. Vol. 16, nr 2, s. 187-195
Emneord [en]
Neural networks, Kernel ridge regression, Support vector regression, Offset printing, Colour print quality
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Identifikatorer
URN: urn:nbn:se:hh:diva-2063DOI: 10.1007/s00521-006-0066-6ISI: 000244199900009Scopus ID: 2-s2.0-33847284030Lokal ID: 2082/2458OAI: oai:DiVA.org:hh-2063DiVA, id: diva2:239281
Tilgjengelig fra: 2008-10-18 Laget: 2008-10-18 Sist oppdatert: 2018-03-23bibliografisk kontrollert

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