System for assessing, exploring and monitoring offset print quality

Authors:
Jens Lundström;Antanas Verikas
Affiliations:
Intelligent Systems Laboratory, Halmstad University, Halmstad, Sweden;Intelligent Systems Laboratory, Halmstad University, Halmstad, Sweden
Venue:
CSCC'11 Proceedings of the 2nd international conference on Circuits, Systems, Communications & Computers
Year:
2011

Citing 3
Cited 0

Fast noise variance estimation

Computer Vision and Image Understanding
Study on the Offset Color Reproduction Control System Based on Fuzzy Neural Network

ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Review: Advances in computational intelligence-based print quality assessment and control in offset colour printing

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Variations in offset print quality relate to numerous parameters of printing press and paper. To maintain constant quality of products, press operators need to assess, explore and monitor print quality. This paper presents a novel system for assessing and predicting values of print quality attributes, where the adopted, random forests (RF)-based, modeling approach also allows quantifying the influence of different parameters. In contrast to other print quality assessment systems, this system utilizes common print marks known as double grey-bars. A novel virtual sensor for assessing the miss-registration degree of printing plates using images of double grey-bars is presented. The inferred influence of paper and printing press parameters on print quality shows correlation with known print quality conditions.