The Research of Printing Quality Based on Tri stimulus Value

Abstract:

In order to meet the limitation of density detection based on color mixing theory in traditional printing quality control, the study has established a relational model for colorimetric tri-stimulus value and ink feeding volume. It builds a colorimetric mathematical model from the offset printing proof, and uses the regression theory to correct the metring model and determine the dummy blackprint. So it can solve the problem of indeterminate solution in conversion process from tri-stimulus value to dot coverage. It fits the functional relationship through both dot area variation value and dot density variation value accessed via Yule - Nielsen formula so as to connect them. The experiment shows that it is available to get ink volume deviation with standard proof by chromaticity measurement, and there is a significant linear relationship between the corrected Neugebauer equation coefficient and tri-stimulus value. After normalizing the precision of Neugebauer equation which has been improved, the nonlinear relationship exists both in density variation value and area variation value, and the precision of the model is well and can be applied to the actual manufacture.

• Periodical: Advanced Materials Research (Volumes 317-319)
• Pages: 1701-1705
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.317-319.1701
• Online since: August 2011
• Authors: Kai Li, Yuan Du
• Keywords: Neugebauer Equation, Printing Quality, Tri-Stimulus Value

References

[1] Liu Shichang. The measurement and control of printing. Graphic Communication Press, 2 (2004).

[2] Zhou Shisheng, Zheng Yuanlin, Cao Congjun and Qi Yonghong. Printing Chromatics, Graphic Communication Press, 3 (2005).

[3] Zheng Yuanlin, Flexo four-color printing coloration mathematical model. Xi'an University of Technology Master's thesis, 2002.

[4] Richard L. Burden and J. Douglas Faires. Numerical Analysis. Higher Education Press, 5 (2008).

[5] Feng Jian, Flexo Printing coloration mathematical model and its application. Xi'an University of Technology Master's thesis, 2001.

[6] Wang Rongxin, Mathematical Statistics. Xi'an JiaoTong University Press, 9 (2006).