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A Study of Oriented Mottle in Halftone Print
Linköping University, Department of Science and Technology.
Linköping University, Department of Science and Technology.
2007 (English)Independent thesis Advanced level (degree of Magister), 20 points / 30 hpStudent thesis
Abstract [en]

Coated solid bleached board belongs to the top-segment of paperboards. One important property of paperboard is the printability. In this diploma work a specific print defect, oriented mottle, has been studied in association with Iggesund Paperboard. The objectives of the work were to develop a method for analysis of the dark and light areas of oriented mottle, to analyse these areas, and to clarify the effect from the print, coating and paperboard surface related factors. This would clarify the origin of oriented mottle and predict oriented mottle on unprinted paperboard. The objectives were fulfilled by analysing the areas between the dark halftone dots, the amount of coating and the ink penetration, the micro roughness and the topography. The analysis of the areas between the dark halftone dots was performed on several samples and the results were compared regarding different properties. The other methods were only applied on a limited selection of samples. The results from the study showed that the intensity differences between the dark halftone dots were enhanced in the dark areas, the coating amount was lower in the dark areas and the ink did not penetrate into the paperboard. The other results showed that areas with high transmission corresponded to dark areas, smoother micro roughness, lower coating amount and high topography. A combination of the information from these properties might be used to predict oriented mottle. The oriented mottle is probably an optical phenomenon in half tone prints, and originates from variations in the coating and other paperboard properties.

Place, publisher, year, edition, pages
Institutionen för teknik och naturvetenskap , 2007. , 122 p.
Keyword [en]
Printing, Mottle, Image Processing, Paper technology
National Category
Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:liu:diva-9233ISRN: LITH-ITN-MT-MX--07/024--SEOAI: diva2:23814
2007-05-02, Norrköping, 10:15
Available from: 2007-06-14 Created: 2007-06-14

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