This invited talk summarizes computer vision based research and applications for forest industry developed by Machine and Pattern Recognition Laboratory (MVPR) at Lappeenranta University of Technology (LUT) in Finland. The main focus is on the paper and board making industry. Our approach is application-oriented based on practical industrial needs. Typically industrial manufacturing consists of several process steps. At each step it is important to recognize important phenomena affecting production, to measure these phenomena, and finally, to analyze these measurements for the further control of the production. In this presentation it is shown how machine vision can be used for vision-based quality management in the papermaking industry. The objective of the research is the overall management of the whole papermaking process and the quality assessment of the paper-based end product before and after printing. The general goal is that the production is resource-efficient and environmentally sound, using less raw material, water, and energy.
Paper is a challenging media to use due to paper characteristics which affect very much printing quality. Thus, it is important to predict the quality of printing on paper or board, especially in case of images. It is necessary that printed materials look good enough to a consumer. For example, advertisement must obtain positive attention and a high-quality journal to be comfortable to read. Thus, a paper manufacturer should know which kind of quality it offers to a printing house. The quality should not be too high or too low but just sufficient for a known purpose, i.e., so called the wanted quality. Solving this problem leads to the need of the quality assessment before printing and after printing. In the both cases the visual quality assessment is usually done by manually or semiautomatically either observing manufacturing processes or test prints. In this presentation, machine vision solutions are considered where the quality prediction is performed using automatic image processing and analysis systems, without the human interaction, used in the different process steps of pulping, papermaking, and printing. The results obtained from industrial research projects consist of on-line control solutions in industrial manufacturing, off-line laboratory level tests, and frameworks for modeling connections between human perception and physical measurements based on the overall visual quality index of an image or on the regions of interest in an image.