Computational Evaluation of Print Unevenness According to Human Vision

Print quality and the printability of paper are very important attributes when modern printing applications are considered. In prints containing images, high print quality is a basic requirement. Tone unevenness and non uniform glossiness of printed products are the most disturbing factors influencing overall print quality. These defects are caused by non ideal interactions of paper, ink and printing devices in high speed printing processes. Since print quality is a perceptive characteristic, the measurement of unevenness according to human vision is a significant problem. In this thesis, the mottling phenomenon is studied. Mottling is a printing defect characterized by a spotty, non uniform appearance in solid printed areas. Print mottle is usually the result of uneven ink lay down or non uniform ink absorption across the paper surface, especially visible in mid tone imagery or areas of uniform color, such as solids and continuous tone screen builds. By using existing knowledge on visual perception and known methods to quantify print tone variation, a new method for print unevenness evaluation is introduced. The method is compared to previous results in the field and is supported by psychometric experiments. Pilot studies are made to estimate the effect of optical paper characteristics prior to printing, on the unevenness of the printed area after printing. Instrumental methods for print unevenness evaluation have been compared and the results of the comparison indicate that the proposed method produces better results in terms of visual evaluation correspondence. The method has been successfully implemented as ail industrial application and is proved to be a reliable substitute to visual expertise.

Machine vision methods for process measurements in pulping

The papermaking industry has been continuously developing intelligent solutions to characterize the raw materials it uses, to control the manufacturing process in a robust way, and to guarantee the desired quality of the end product. Based on the much improved imaging techniques and image-based analysis methods, it has become possible to look inside the manufacturing pipeline and propose more effective alternatives to human expertise. This study is focused on the development of image analyses methods for the pulping process of papermaking. Pulping starts with wood disintegration and forming the fiber suspension that is subsequently bleached, mixed with additives and chemicals, and finally dried and shipped to the papermaking mills. At each stage of the process it is important to analyze the properties of the raw material to guarantee the product quality. In order to evaluate properties of fibers, the main component of the pulp suspension, a framework for fiber characterization based on microscopic images is proposed in this thesis as the first contribution. The framework allows computation of fiber length and curl index correlating well with the ground truth values. The bubble detection method, the second contribution, was developed in order to estimate the gas volume at the delignification stage of the pulping process based on high-resolution in-line imaging. The gas volume was estimated accurately and the solution enabled just-in-time process termination whereas the accurate estimation of bubble size categories still remained challenging. As the third contribution of the study, optical flow computation was studied and the methods were successfully applied to pulp flow velocity estimation based on double-exposed images. Finally, a framework for classifying dirt particles in dried pulp sheets, including the semisynthetic ground truth generation, feature selection, and performance comparison of the state-of-the-art classification techniques, was proposed as the fourth contribution. The framework was successfully tested on the semisynthetic and real-world pulp sheet images. These four contributions assist in developing an integrated factory-level vision-based process control.

m-Equine : IS support for the horse industry

The horse industry is in many ways still operating the same way as it did in the beginning of the 20th century. At the same time the role of the horse has changed dramatically, from a beast of burden to a top athlete, a production animal or a beloved pet. A racehorse or an equestrian sport horse is trained and taken care of like any other athlete, but unlike its human counterpart, it might end up on our plate. According to European and many other countries’ laws, a horse is a production animal. The medical data of a horse should be known if it is to be slaughtered, to ensure that the meat is safe for human consumption. Today this vital medical information should be noted in the horse’s passport, but this paperbased system is not reliable. If a horse gets sold, depending on the country’s laws, the medical records might not be transferred to the new owner, the horse’s passport might get lost etc. Thus the system is not fool proof. It is not only the horse owners who have to struggle with paperwork; veterinarians as well as other officials often use much time on redundant paperwork. The main research question of this thesis is if IS could be used to help the different stakeholders within the horse industry? Veterinarians in particular who travel to stables to treat horses cannot always take with them their computers, since the somewhat unsanitary environment is not suitable for a sensitive technological device. Currently there is no common medical database developed for horses, although such a database with a support system could help with many problems. These include vaccination and disease control, food-safety, as well as export and import problems. The main stakeholders within the horse industry, including equine veterinarians and horse owners, were studied to find out their daily routines and needs for a possible support system. The research showed that there are different aspects within the horse industry where IS could be used to support the stakeholders daily routines. Thus a support system including web and mobile accessibility for the main stakeholders is under development. Since veterinarians will be the main users of this support system, it is very important to make sure that they find it useful and beneficial in their daily work. To ensure a desired result, the research and development of the system has been done iteratively with the stakeholders following the Action Design Research methodology.

Sustainable Computer Science Education

As the world becomes more technologically advanced and economies become globalized, computer science evolution has become faster than ever before. With this evolution and globalization come the need for sustainable university curricula that adequately prepare graduates for life in the industry. Additionally, behavioural skills or “soft” skills have become just as important as technical abilities and knowledge or “hard” skills. The objective of this study was to investigate the current skill gap that exists between computer science university graduates and actual industry needs as well as the sustainability of current computer science university curricula by conducting a systematic literature review of existing publications on the subject as well as a survey of recently graduated computer science students and their work supervisors. A quantitative study was carried out with respondents from six countries, mainly Finland, 31 of the responses came from recently graduated computer science professionals and 18 from their employers. The observed trends suggest that a skill gap really does exist particularly with “soft” skills and that many companies are forced to provide additional training to newly graduated employees if they are to be successful at their jobs.