A color proving system for printing press using image processing and expert opinion

Main Article Content

ไกรฤกษ์ เชยชื่น
พิชิต กิตติสุวรรณ์

Abstract

This paper presents a system of color proving for printing press performed by the expert with longer experiences. The traditional process will be performed with high risk in the case of lack the expert and may affect to publisher. In this paper, we propose a design and development of an automatic system for simple color proving in the process of press making using image processing under opinion of the expert. The expert system was embedded in a controller and trained by sampling color images with various conditions of lighting environments for printing press. The selected images will be scored by the experts from a printing press company and all color histograms will be computed to build standard color histogram for a printing press. In testing process, the standard histogram will be compared with the testing samples to evaluate quality of color. For experiment, we divided experiment into  2  experiments:  1. the experiment to make the standard color histogram and 2. the experiment to evaluate quality of the printing press. The experiments show the system has 22.22% error for evaluating quality of the printing press caused by uncertainty of lighting environment in experiment room. The uncertainty of the lighting affects high variance of standard color histogram.

Article Details

How to Cite
เชยชื่น ไ., & กิตติสุวรรณ์ พ. (2019). A color proving system for printing press using image processing and expert opinion. Rattanakosin Journal of Science and Technology, 1(1), 1–11. Retrieved from https://ph02.tci-thaijo.org/index.php/RJST/article/view/185456
Section
Research Articles

References

1. M. C. Stone, W. B. Cowan, and J. C. Beatty, “Color Gamut Mapping and the Printing of Digital Color Image,” ACM Transactions on Graphics, Vol.7, No.4, p.249-292, 1988.

2. J. Luo and Z. Zhang, “Automatic color printing inspection by image processing,” Journal of Materials Processing Technology, Vol.139, p.373-378, 2003.

3. A. Verikas and M. Bacauskene, “Image analysis and fuzzy integration applied to print quality assessment,” International Journal on Cybernetics and Systems, Vol.36, p.549-564, 2005.

4. N. Mostafa and M. Mostafa, “Printing Quality Enhancement According to ISO12647-2 (Applying in One of Egyptian Printing-Houses),” International design Journal, 2016.

5. S. McKenna, S. Jabri, Z. Doric, H. Wechsler and A. Rosenfeldf, “Tracking Groups of People,” Journal of Computer Vision and Image Understanding, Vol. 80, No.1, pp. 42-56, 2000.