Evaluation of Systematic&Colour Print Mottle

Detta är en Uppsats för yrkesexamina på grundnivå från Linköpings universitet/Institutionen för teknik och naturvetenskap

Sammanfattning: Print mottle is a problem that has been hassling the printing business for a long time. Along with sharpness and correct colour reproduction, absence of print mottle is one of the most important factors of print quality. The possibility to measure the amount of print mottle (reflectance variation) may in many ways facilitate the development of printing methods. Such a measurement model should preferably follow the functions and abilities of the Human Visual System (HVS). The traditional model that STFI-Packforsk has developed to measure print mottle uses frequency analysis to find variations in reflectance. However, this model suffers some limitations since is does not perfectly agree with the functions of the HVS and does only measure variations in lightness. A new model that better follows the functions of the HVS has thus been developed. The new model does not only consider variations in lightness (monochromatic) but also variations in colour (chromatic). The new model also puts a higher weight on systematic variations than on random variations since the human eye is more sensitive to ordered structures. Furthermore, the new model uses a contrast sensitivity function that weights the importance of variations in different frequencies. To compare the new model with the traditional STFI model, two tests were carried out. Each test consisted of a group of test patches that were evaluated by the traditional STFI model and the new model. The first test consisted of 15 greyscale test patches that originated from conventional flexo and offset presses. The second test consisted of 24 digitally simulated test patches containing colour mottle and systematic mottle. The evaluation results in both the traditional and the new model were compared to the results of a visual evaluation carried out using a panel of test persons. The new model produced a result that correlated considerably better with the visual estimation than what the traditional model did.

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