New Distance Transforms for Gray Level Image Compression

This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4

Examining the Role of Rebranding in Perceived Image of a Product Line

The main objective for this study was to explore certain organization’s product line rebranding process and its impact on product line’s perceived image. The case company is a global paper, packaging and forest products company, business segment paper board. The audience explored is one of the company’s major customers, merchant in Germany. The research was performed as a descriptive case study with a purpose to provide longitudinal insight into the product line image and its eventual alteration as a result of the case company’s rebranding process. Mainly qualitative methods were used for conducting the research. The data for the empirical part was collected with a web-based survey at two different points of time; before the rebranded products entered the market and after they had been available approximately six months. The results of this study reveal that the case company has performed well in its attempt to improve product line’s brand image through rebranding. It was found that between the two brand image measurements the product brand image seems to have improved in all of the areas which according to theoretical framework of this study contribute to formation of brand image; brand associations, marketing communications and interpersonal relationships, not forgetting the original platform that initiated the change; technical quality modifications. In other words it may be concluded that as technical quality was brought to a new level, also assessments about the brand image improved respectively.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Liquid transportation and distribution during (re)wetting : impact on coated papers in printing

In many industrial applications, such as the printing and coatings industry, wetting of porous materials by liquids includes not only imbibition and permeation into the bulk but also surface spreading and evaporation. By understanding these phenomena, valuable information can be obtained for improved process control, runnability and printability, in which liquid penetration and subsequent drying play important quality and economic roles. Knowledge of the position of the wetting front and the distribution/degree of pore filling within the structure is crucial in describing the transport phenomena involved. Although exemplifying paper as a porous medium in this work, the generalisation to dynamic liquid transfer onto a surface, including permeation and imbibition into porous media, is of importance to many industrial and naturally occurring environmental processes. This thesis explains the phenomena in the field of heatset web offset printing but the content and the analyses are applicable in many other printing methods and also other technologies where water/moisture monitoring is crucial in order to have a stable process and achieve high quality end products. The use of near-infrared technology to study the water and moisture response of porous pigmented structures is presented. The use of sensitive surface chemical and structural analysis, as well as the internal structure investigation of a porous structure, to inspect liquid wetting and distribution, complements the information obtained by spectroscopic techniques. Strong emphasis has been put on the scale of measurement, to filter irrelevant information and to understand the relationship between interactions involved. The near-infrared spectroscopic technique, presented here, samples directly the changes in signal absorbance and its variation in the process at multiple locations in a print production line. The in-line non-contact measurements are facilitated by using several diffuse reflectance probes, giving the absolute water/moisture content from a defined position in the dynamic process in real-time. The nearinfrared measurement data illustrate the changes in moisture content as the paper is passing through the printing nips and dryer, respectively, and the analysis of the mechanisms involved highlight the roles of the contacting surfaces and the relative liquid carrier properties of both non-image and printed image areas. The thesis includes laboratory studies on wetting of porous media in the form of coated paper and compressed pigment tablets by mono-, dual-, and multi-component liquids, and paper water/moisture content analysis in both offline and online conditions, thus also enabling direct sampling of temporal water/moisture profiles from multiple locations. One main focus in this thesis was to establish a measurement system which is able to monitor rapid changes in moisture content of paper. The study suggests that near-infrared diffuse reflectance spectroscopy can be used as a moisture sensitive system and to provide accurate online qualitative indicators, but, also, when accurately calibrated, can provide quantification of water/moisture levels, its distribution and dynamic liquid transfer. Due to the high sensitivity, samples can be measured with excellent reproducibility and good signal to noise ratio. Another focus of this thesis was on the evolution of the moisture content, i.e. changes in moisture content referred to (re)wetting, and liquid distribution during printing of coated paper. The study confirmed different wetting phases together with the factors affecting each phase both for a single droplet and a liquid film applied on a porous substrate. For a single droplet, initial capillary driven imbibition is followed by equilibrium pore filling and liquid retreat by evaporation. In the case of a liquid film applied on paper, the controlling factors defining the transportation were concluded to be the applied liquid volume in relation to surface roughness, capillarity and permeability of the coating giving the liquid uptake capacity. The printing trials confirmed moisture gradients in the printed sheet depending on process parameters such as speed, fountain solution dosage and drying conditions as well as the printed layout itself. Uneven moisture distribution in the printed sheet was identified to be one of the sources for waving appearance and the magnitude of waving was influenced by the drying conditions.

Characterization of fiber and vessel elements in pulp suspension images

The thesis is related to the topic of image-based characterization of fibers in pulp suspension during the papermaking process. Papermaking industry is focusing on process control optimization and automatization, which makes it possible to manufacture highquality products in a resource-efficient way. Being a part of the process control, pulp suspension analysis allows to predict and modify properties of the end product. This work is a part of the tree species identification task and focuses on analysis of fiber parameters in the pulp suspension at the wet stage of paper production. The existing machine vision methods for pulp characterization were investigated, and a method exploiting direction sensitive filtering, non-maximum suppression, hysteresis thresholding, tensor voting, and curve extraction from tensor maps was developed. Application of the method to the microscopic grayscale pulp images made it possible to detect curves corresponding to fibers in the pulp image and to compute their morphological characteristics. Performance of the method was evaluated based on the manually produced ground truth data. An accuracy of fiber characteristics estimation, including length, width, and curvature, for the acacia pulp images was found to be 84, 85, and 60% correspondingly.

Training executive functions in the laboratory and in real life : cognitive consequences of computer-based exercises and bilingualism

The question of the trainability of executive functions and the impact of such training on related cognitive skills has stirred considerable research interest. Despite a number of studies investigating this, the question has not yet been solved. The general aim of this thesis was to investigate two very different types of training of executive functions: laboratory-based computerized training (Studies I-III) and realworld training through bilingualism (Studies IV-V). Bilingualism as a kind of training of executive functions is based on the idea that managing two languages requires executive resources, and previous studies have suggested a bilingual advantage in executive functions. Three executive functions were studied in the present thesis: updating of working memory (WM) contents, inhibition of irrelevant information, and shifting between tasks and mental sets. Studies I-III investigated the effects of computer-based training of WM updating (Study I), inhibition (Study II), and set shifting (Study III) in healthy young adults. All studies showed increased performance on the trained task. More importantly, improvement on an untrained task tapping the trained executive function (near transfer) was seen in Study I and II. None of the three studies showed improvement on untrained tasks tapping some other cognitive function (far transfer) as a result of training. Study I also used PET to investigate the effects of WM updating training on a neurotransmitter closely linked to WM, namely dopamine. The PET results revealed increased striatal dopamine release during WM updating performance as a result of training. Study IV investigated the ability to inhibit task-irrelevant stimuli in bilinguals and monolinguals by using a dichotic listening task. The results showed that the bilinguals exceeded the monolinguals in inhibiting task-irrelevant information. Study V introduced a new, complementary research approach to study the bilingual executive advantage and its underlying mechanisms. To circumvent the methodological problems related to natural groups design, this approach focuses only on bilinguals and examines whether individual differences in bilingual behavior correlate with executive task performances. Using measures that tap the three above-entioned executive functions, the results suggested that more frequent language switching was associated with better set shifting skills, and earlier acquisition of the second language was related to better inhibition skills. In conclusion, the present behavioral results showed that computer-based training of executive functions can improve performance on the trained task and on closely related tasks, but does not yield a more general improvement of cognitive skills. Moreover, the functional neuroimaging results reveal that WM training modulates striatal dopaminergic function, speaking for training-induced neural plasticity in this important neurotransmitter system. With regard to bilingualism, the results provide further support to the idea that bilingualism can enhance executive functions. In addition, the new complementary research approach proposed here provides some clues as to which aspects of everyday bilingual behavior may be related to the advantage in executive functions in bilingual individuals.

Content marketing and the significance of corporate branding

Tämän tutkielman tavoite on tutkia vahvan brandin merkitystä ja syitä, miksi yritykset käyttävät sisältömarkkinointia brandin rakentamisessa, sekä selvittää mitkä ovat yritysten sisältömarkkinointi-investointien tavoitteet, odotetut seuraukset ja koetut hyödyt ja tulokset. Teoriaosassa esitetään empiriaosaa varten tarvittava akateeminen taustatutkimustieto. Empiria on toteutettu puoli-struktroiduilla kahdenkeskisillä puhelinhaastatteuilla. Haastateltavina ovat työn toimeksiantajan Calcus Kustannus Oy:n viisi asiakasta. Näiden yritysten liikevaihto vaihtelee 23-75M€ välillä, ja yritykset toimivat pääosin suomen B2B yritysmarkkinoilla. Haastateltavat henkilöt ovat yrityksissä vastuussa markkinointipäätöksistä. Tulokset osoittavat, että vahvalla brandilla on erittäin suuri merkitys yrityksen kasvun ja menestyksen kannalta, ja että yritykset käyttävät sisältömarkkinointia brandin rakentamisessa, koska se kasvattaa brandipääomaa tehokkaasti. Sisältömarkkinoinnilla yritykset pyrkivät kasvttamaan heidän asiakkaidensa branditietoisuutta ja brandiuskollisuutta, sekä brandinsa uskottavuutta jakamalla aidosti kiinnostavaa ja lisäarvoa tuottavaa sisältöä. Lisäksi yrityksen asiantuntija-, sekä mielipidejohtajaroolin vahvistaminen koettiin erittäin tärkeäksi. Sisältömarkkinoinnin koetaan olevan brandin rakentamisessa tehokkaampaa kuin traditionaalinen markkinointi, minkä vuoksi yritykset tulevat kasvattamaan sen osuutta markkinointisuunnitelmissaan tulevaisuudessa.

Model-Based Tracking Initialization in Ship Building Environment

An augmented reality (AR) device must know observer’s location and orientation, i.e. observer’s pose, to be able to correctly register the virtual content to observer’s view. One possible way to determine and continuously follow-up the pose is model-based visual tracking. It supposes that a 3D model of the surroundings is known and that there is a video camera that is fixed to the device. The pose is tracked by comparing the video camera image to the model. Each new pose estimate is usually based on the previous estimate. However, the first estimate must be found out without a prior estimate, i.e. the tracking must be initialized, which in practice means that some model features must be identified from the image and matched to model features. This is known in literature as model-to-image registration problem or simultaneous pose and correspondence problem. This report reviews visual tracking initialization methods that are suitable for visual tracking in ship building environment when the ship CAD model is available. The environment is complex, which makes the initialization non-trivial. The report has been done as part of MARIN project.

Distributed Repositories of Medieval Calendars and Crowd-Sourcing of Transcription

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Formation of the Employer Brand Image

The purpose of this study was to explore the employer brand image and its formation of a Finnish (yet international) service company in B2B sector. In the research qualitative case study method was used to explore the most preferred attributes in employer attraction, the employer brand perceptions towards the case company, and the effectors behind these brand perceptions among the prospective group of employees. The research was conducted through in-depth semistructured interviews among 23-30 undergraduate or graduate business students in Finnish universities close to their graduation. After deriving the attributes of an attractive employer, and exploring their relation to the case company, the employer brand image of the case company was determined and its attractiveness level evaluated. Moreover, the formation of the employer brand image was investigated and its sources detected. The most important factors for the target group in employer attractiveness were found to be company reputation and company culture/work atmosphere. Also career opportunities and international opportunities were seen important. The case company was found to hold a positive, attractive image on company culture and international opportunities, but failing to hold a good reputation as a fair employer. The main and most impactful source of employer brand image was former and current employees - directly or indirectly. Company’s own actions played only small part in employer brand formation as credibility is a critical factor in brand image formation and corporate communication found not to be perceived genuine. Based on the findings, suggestions for further employer branding were made.

Internal Employer Brand: The factors affecting the formation of internal employer image

The purpose of this study is to identify the factors affecting the formation of employer image and attractiveness in the minds of an organization’s employees. Six employees from different backgrounds and business units within a larger organization are interviewed, and the results are compared in order to better understand the effect divergent variables have on the resulting factors. The theoretical background of the research is based on the study of the concept of employer branding, an organization’s effort in affecting the employer image it projects and attractiveness perceived by the employees and applicants. The results of the study reveal how immaterial factors, primarily related to self-actualization and social relationships, often took precedence over material ones, so long as the material factors, such as salary and work equipment, were at least on a minimum level acceptable to the employee. As such, focusing on these immaterial factors when forming an employer brand strategy is expected to yield larger benefits in form of employer attractiveness.