Coated solid bleached board belongs to the top-segment of paperboards. One important property of paperboard is the printability. In this diploma work a specific print defect, oriented mottle, has been studied in association with Iggesund Paperboard. The objectives of the work were to develop a method for analysis of the dark and light areas of oriented mottle, to analyse these areas, and to clarify the effect from the print, coating and paperboard surface related factors. This would clarify the origin of oriented mottle and predict oriented mottle on unprinted paperboard. The objectives were fulfilled by analysing the areas between the dark halftone dots, the amount of coating and the ink penetration, the micro roughness and the topography. The analysis of the areas between the dark halftone dots was performed on several samples and the results were compared regarding different properties. The other methods were only applied on a limited selection of samples. The results from the study showed that the intensity differences between the dark halftone dots were enhanced in the dark areas, the coating amount was lower in the dark areas and the ink did not penetrate into the paperboard. The other results showed that areas with high transmission corresponded to dark areas, smoother micro roughness, lower coating amount and high topography. A combination of the information from these properties might be used to predict oriented mottle. The oriented mottle is probably an optical phenomenon in half tone prints, and originates from variations in the coating and other paperboard properties.

Initially an analytical closed-form inverse kinematics solution for a 5 DOF robotic arm was developed and implemented. This analytical solution proved not to meet the accuracy required for the shape sorting puzzle setup used in the COSPAL (COgnitiveSystems using Perception-Action Learning) project [2]. The correctness of the analytic model could be confirmed through a simulated ideal robot and the source of the problem was deemed to be nonlinearities introduced by weak servos unable to compensate for the effect of gravity. Instead of developing a new analytical model that took the effect of gravity into account, which would be erroneous when the characteristics of the robotic arm changed, e.g. when picking up a heavy object, a learning approach was selected. As learning method Locally Weighted Projection Regression (LWPR) [27] is used. It is an incremental supervised learning method and it is considered a state-ofthe-art method for function approximation in high dimensional spaces. LWPR is further combined with visual servoing. This allows for an improvement in accuracy by the use of visual feedback and the problems introduced by the weak servos can be solved. By combining the trained LWPR model with visual servoing, a high level of accuracy is reached, which is sufficient for the shape sorting puzzle setup used in COSPAL.

This thesis investigates how disparity estimation may be used to visualize an object on a 3D-screen. The first part looks into different methods of disparity estimation, and the second part examines different ways to visualize an object from one or several stereo pairs and a disparity map. Input to the system is one or several stereo pairs, and output is a sequence of images of the input scene but from more angles. This sequence of images can be shown on Setred AB's 3D-screen. The system has high real time demands and the goal is to do the disparity estimation and visualization in real time. In the first part of the thesis, three different ways to calculate disparity maps are implemented and compared. The three methods are correlation-based, local structure-based and phase-based techniques. The correlation-based methods cannot satisfy the real-time demands due to the large number of 2D-convolutions required per pixel. The local structure-based methods have too much noise and cannot satisfy the quality requirements. Therefore, the best method by far is the phase-based method. This method has been implemented in Matlab and C and comparisons between the different implementations are presented. The quality of the disparity maps is satisfying, but the real-time demands cannot yet be fulfilled. The future work is therefore to optimize the C code and move some functions to a GPU, because a GPU can perform calculations in parallel with the CPU. Another reason is that many of the calculations are related to resizing and warping, which are well-suited to implementation on a GPU.

The increased usage of infrared sensors by pilots has created a growing demand for simulated environments based on infrared radiation. This has led to an increased need for Saab to refine their existing model for simulating real-time infrared imagery, resulting in the carrying through of this thesis. Saab develops the Gripen aircraft, and they provide training simulators where pilots can train in a realistic environment. The new model is required to be based on the real-world behavior of infrared radiation, and furthermore, unlike Saab's existing model, have dynamically changeable attributes. This thesis seeks to develop a simulation model compliant with the requirements presented by Saab, and to develop the implementation of a test environment demonstrating the features and capabilities of the proposed model. All through the development of the model, the pilot training value has been kept in mind. The first part of the thesis consists of a literature study to build a theoretical base for the rest of the work. This is followed by the development of the simulation model itself and a subsequent implementation thereof. The simulation model and the test implementation are evaluated as the final step conducted within the framework of this thesis. The main conclusions of this thesis first of all includes that the proposed simulation model does in fact have its foundation in physics. It is further concluded that certain attributes of the model, such as time of day, are dynamically changeable as requested. Furthermore, the test implementation is considered to have been feasibly integrated with the current simulation environment. A plan concluding how to proceed has also been developed. The plan suggests future work with the proposed simulation model, since the evaluation shows that it performs well in comparison to the existing model as well as other products on the market.

This study is aming to examine how municipal instances understand and work to prevent violent extremism. The study illustrates how the local coordinator in a swedish municipality together with representatives from the social service, the school and the police work against autonomous left, white power environment and violent Islamist extremists. I have used Sahlins (2000) theory of crime prevention and Lipskys (2010) theory of street level bureaucracies to analyze the empirical.  To get a deeper understanding how the actors define and work with the problem I have used semistrutcured interviews with a local coordinator, two polices, two field assistants, two polices and one teacher. Even if violent extremism is expression of political opinion or religious belief the municipality means that alienation is the reason why people involve themselves in violent extremism. As a consequense the municipality have integrated the preventing work in their regular crimepreventing work.   The prevention work is characterized of both workdivision, where each profession mind its own working area, and cooperation, wich gives a good view of the situation in the municipality. Since there are consensus that the main goal is to prevent alienation the study picturize a functioning cooperation with few conflicts between the professions that is included in this crimepreventing work. / Denna studie syftar till att undersöka hur kommunala instanser förstår och arbetar för att motverka våldsbejakande extremism. Studien belyser hur den lokala samordnaren i en svensk kommun tillsammans med och representanter från socialtjänsten, skolan och polisen arbetar mot tre grupper; autonoma miljön, vit makt-miljön, och våldsbejakande islamistiska extremistiska miljön.   De teoretiska ramverk som använts som verktyg och hjälpmedel för att analysera empirin är Sahlins (2000) teori om brottsprevention samt Lipskys (2010) teori om gräsrotsbyråkrater. För att få en djupare förståelse hur de lokala aktörerna definierar och arbetar med problemet har studien genomförts med hjälp av semistrukturerade intervjuer med en lokal samordnare, två poliser, två fältassistenter och en lärare.   Även om våldsbejakande extremism är uttryck för politisk åsikt eller religiös tro menar kommunen att orsaken till att människor söker sig till dessa grupper är känslan av utanförskap. Som en konsekvens av detta har kommunen integrerat arbetet mot våldsbejakande extremism i sin befintliga brottsförebyggande verksamhet. Arbetet präglas av både arbetsdelning, där varje yrkeskategori arbetar utifrån sitt specifika mandat på sin egen arena, och samverkan, vilket ger en god helhetsbild av läget i kommunen. Då det finns en samsyn kring att det prioriterade målet är att motverka utanförskap visar studien på ett fungerande samarbete med få konflikter mellan de yrkesgrupper som ingår i detta brottsförebyggande arbete.

Object recognition is a much studied computer vision problem, where the task is to find a given object in an image. This Master Thesis aims at doing a MATLAB implementation of an object recognition algorithm that finds three kinds of objects in images: electrical outlets, light switches and wall mounted air-conditioning controls. Visually, these three objects are quite similar and the aim is to be able to locate these objects in an image, as well as being able to distinguish them from one another. The object recognition was accomplished using Histogram of Oriented Gradients (HOG). During the training phase, the program was trained with images of the objects to be located, as well as reference images which did not contain the objects. A Support Vector Machine (SVM) was used in the classification phase. The performance was measured for two different setups, one where the training data consisted of photos and one where the training data consisted of digitally generated images created using a 3D modeling software, in addition to the photos. The results show that using digitally generated images as training images didn’t improve the accuracy in this case. The reason for this is probably that there is too little intraclass variability in the gradients in digitally generated images, they’re too synthetic in a sense, which makes them poor at reflecting reality for this specific approach. The result might have been different if a higher number of digitally generated images had been used.

Several automatic methods exist for creating 3D point clouds extracted from 2D photos. In manycases, the result is a sparse point cloud, unevenly distributed over the scene.After determining the coordinates of the same point in two images of an object, the 3D positionof that point can be calculated using knowledge of camera data and relative orientation. A model created from a unevenly distributed point clouds may loss detail and precision in thesparse areas. The aim of this thesis is to study methods for densification of point clouds. This thesis contains a literature study over different methods for extracting matched point pairs,and an implementation of Least Square Template Matching (LSTM) with a set of improvementtechniques. The implementation is evaluated on a set of different scenes of various difficulty. LSTM is implemented by working on a dense grid of points in an image and Wallis filtering isused to enhance contrast. The matched point correspondences are evaluated with parameters fromthe optimization in order to keep good matches and discard bad ones. The purpose is to find detailsclose to a plane in the images, or on plane-like surfaces. A set of extensions to LSTM is implemented in the aim of improving the quality of the matchedpoints. The seed points are improved by Transformed Normalized Cross Correlation (TNCC) andMultiple Seed Points (MSP) for the same template, and then tested to see if they converge to thesame result. Wallis filtering is used to increase the contrast in the image. The quality of the extractedpoints are evaluated with respect to correlation with other optimization parameters and comparisonof standard deviation in x- and y- direction. If a point is rejected, the option to try again with a largertemplate size exists, called Adaptive Template Size (ATS).

3D cameras delivering height data can be used for quality inspection of goods on a conveyor. It is then of interest to distinguish the important parts of the image from background and noise and further to divide these interesting parts into segments that have a strong correlation to objects on the conveyor belt. Segmentation can easily be done by thresholding in the simple case. However, in more complex situations, for example when objects touch or overlap, this does not work well. In this thesis, research and evaluation of a few different methods for segmentation of height image data are presented. The focus is to find an accurate method for segmentation of smooth irregularly shaped organic objects such as vegetables or shellfish. For evaluative purposes a database consisting of height images depicting a variety of such organic objects has been collected. We show in the thesis that a conventional gradient magnitude method is hard to beat in the general case. If, however, the objects to be segmented are heavily non-convex with a lot of crests and valleys within themselves one could be better off choosing a normalized least squares method. / 3D-kameror som levererar höjddata kan användas för kvalitetskontroll av varor på ett löpande band. Det är då av intresse att urskilja de viktiga delarna av bilden från bakgrund och brus samt även att dela upp dessa intressanta delar i segment med stark korrelans till objekten på bandet. Segmentering kan utföras genom tröskling i det enkla fallet. I mer komplexa situationer då objekt vidrör eller överlappar varandra blir det svårare. I detta examensarbete presenteras forskning och utvärdering av några olika metoder för segmentering av höjdbildsdata. Fokus ligger på att finna en noggrann metod för segmentering av mjuka släta oregelbundna objekt som grönsaker och skaldjur. I utvärderingssyfte har en databas bestående höjdbilder föreställande lite olika typer av sådana organiska objekt samlats in. Vi visar i uppstatsen att en konventionell gradientlängdsmetod är svår att slå i det generella fallet. Om objekten som ska segmenteras är kraftigt icke-konvexa å andra sidan, med en mängd krön och dalar inom varje objekt, kan man göra bättre i att välja en normaliserad minstakvadratfelsmetod.

Detta examensarbete tittar närmare på vägplaneringsproblemet som är ett vanligt förekommande problem inom datorspel. Arbetet skall försöka besvara följande frågeställning: Vilka kombinationer av styrbeteenden och beräkningsmodeller kan användas för större grupper av autonoma agenter som navigerar i en miljö med avseende på prestanda och estetik? För att besvara frågeställningen så skapades en applikation där fyra olika styrbeteenden implementerades. Vägföljningsbeteendet är grundbeteendet för agenternas navigering och flockbeteendet används för att ge ett bättre resultat. Resultatet av arbetet visar på att de fyra styrbeteendena som omfattas av arbetet är tillräckligt i de flesta fall; även om det finns brister. De fyra styrbeteendena hade med god anledning kunnat kombinerats med andra styrbeteenden som inte tas upp i arbetet för att ge en mer komplett navigering. Styrbeteenden kan även användas utanför datorspel, så som inom robotik eller för att simulera agenter i en trafikmiljö eller agenter som evakuerar en byggnad.

The main purpose of this work is to reconstruct 3D model of an entire scene byusing two ordinary cameras. We develop a mobile phone application, based onstereo vision and image analysis algorithms, executed either locally or on a remotehost, to calculate the dietary intake using the current questionnaire and the mobilephone photographs. The information of segmented 3D models are used to calculatethe volume -and then the calories- of a person’s daily intake food. The method ischecked using different solid food samples, in different camera arrangements. Theresults shows that the method successfully reconstructs 3D model of different foodsample with high details.