Colorlab Workshop #4: Machine vision and color printing
The workshop is organized by The Norwegian Color Research Laboratory and takes place at Gjøvik University College (GUC), in room G302, on Thursday October 27th.
The workshop is free and open to all.
Program
* 10:30 - 11:30 Machine vision based quality control from pulping to paper making for printing , Prof. Heikki Kälviäinen, Lappeenranta University of Technology, Finland
This presentation considers possibilities which machine vision can provide for quality control along the whole manufacturing line of paper and board products. The scope is from pulping to papermaking, mainly for printing. The motivation of this study comes from the necessity to predict the quality of printing on paper or board, especially in case of images. Printed materials should look good enough to a consumer; advertisement must obtain a positive attention and a high-quality journal must to be comfortable to read. Thus, a paper manufacturer should know which kind of quality it offers to a printing house. In this way the production is resource-efficient and environmentally sound, using less raw material, water, and energy. The visual quality assessment is usually done manually or semiautomatically either observing manufacturing processes or test prints. The results obtained from industrial research projects consist of off-line and on-line solutions for industrial manufacturing and laboratory level testing
* 11:30 - 12:30 Lunch
* 12:30 - 13:30 Digital Printing - A Rich Domain for Image Analysis and Pattern Recognition , Prof. Jan Allebach, Purdue University, USA
Printing ecosystems can be loosely divided into two groups: home/office printing and commercial/industrial printing. Home/office printing is characterized by usage models that are highly heterogeneous, consisting of many different relatively small jobs. Home/office printing only became possible with the advent of digital technologies during the 1980s. In contrast, commercial/industrial printing has been an established activity for nearly 500 years. But it is only now during the last decade or so experiencing a transformation to digital technologies. Digital image analysis and pattern recognition have important roles to play in both these ecosystems, starting with the development of the printing system, continuing to inspection during manufacturing, and then once the product is in use, enabling a more rewarding customer experience, and providing an autonomous or semi-autonomous capability to troubleshoot the causes of print quality issues. In this presentation, I will provide an overview of these application areas, illustrated by specific projects that have been conducted in our laboratory.
* 13:30 - 14:00 Discussion
About the Speakers
Heikki Kälviäinen received his M.Sc. degree and Ph.D. degree (Doctor of Technology) in Computer Science in 1989 and 1994, respectively, from Department of Information Technology in Lappeenranta University of Technology (LUT), Lappeenranta, Finland. Since 1996 Kälviäinen has been a Professor of Computer Science. Currently he is a Vice Dean of Faculty of Technology Management, a Head of Department of Information Technology, and a Head of Machine Vision and Pattern Recognition Research Group. Prof. Kälviäinen has been a Visiting Professor in University of Surrey in United Kingdom and in Czech Technical University in Czech Republic. His primary research interests include machine vision, pattern recognition, and image processing and image analysis. Prof. Kälviäinen belongs to the governing board of IAPR, and he is a member of ACM, IEEE, and SPIE.
Jan P. Allebach is Hewlett-Packard Distinguished Professor of Electrical and Computer Engineering at Purdue University. His current research interests include image rendering, image quality, color imaging and color measurement, document aesthetics, and printer forensics. Professor Allebach is a Fellow of the IEEE, the Society for Imaging Science and Technology (IS&T), and SPIE. He has served as Distinguished or Visiting Lecturer for both IS&T and the IEEE Signal Processing Society. Allebach received the Senior (best paper) Award from the IEEE Signal Processing Society, the Bowman Award and the Itek Best Paper Award from IS&T, was named Electronic Imaging Scientist of the Year by IS&T and SPIE, and was named Honorary Member of IS&T, the highest award that IS&T bestows. From Purdue University, he has received six teaching awards, and separate awards for team leadership, mentoring, and research.
