Brown adipose tissue (BAT) is the main tissue involved in non-shivering heat production. A greater understanding of BAT could possibly lead to new ways of prevention and treatment of obesity and type 2 diabetes. The increasing prevalence of these conditions and the problems they cause society and individuals make the study of the subject important. An ongoing study performed at the Turku University Hospital uses images acquired using PET/MRI with 18F-FDG as the tracer. Scans are performed on sedentary and athlete subjects during normal room temperature and during cold stimulation. Sedentary subjects then undergo scanning during cold stimulation again after a six weeks long exercise training intervention. This degree project used images from this study. The objective of this degree project was to examine methods to automatically and objectively quantify parameters relevant for activation of BAT in combined PET/MRI data. A secondary goal was to create images showing glucose uptake changes in subjects from images taken at different times. Parameters were quantified in adipose tissue directly without registration (image matching), and for neck scans also after registration. Results for the first three subjects who have completed the study are presented. Larger registration errors were encountered near moving organs and in regions with less information. The creation of images showing changes in glucose uptake seem to be working well for the neck scans, and somewhat well for other sub-volumes. These images can be useful for identification of BAT. Examples of these images are shown in the report.

Image based modeling using visual images has undergone major development during the earlier parts of the 21th century. In this thesis a system for automated uncalibrated scene reconstruction using infrared images is implemented and tested. An automated reconstruction system could serve to simplify thermal inspection or as a demonstration tool. Thermal images will in general have lower resolution, less contrast and less high frequency content as compared to visual images. These characteristics of infrared images further complicates feature extraction and matching, key steps in the reconstruction process. In order to remedy the complication preprocessing methods are suggested and tested as well. Infrared modeling will also impose additional demands on the reconstruction as it is of importance to maintain thermal accuracy of the images in the product. Three main results are obtained from this thesis. Firstly, it is possible to obtain camera calibration and pose as well as a sparse point cloud reconstruction from an infrared image sequence using the suggested implementation. Secondly, correlation of thermal measurements from the images used to reconstruct three dimensional coordinates is presented and analyzed. Lastly, from the preprocessing evaluation it is concluded that the tested methods are not suitable. The methods will increase computational cost while improvements in the model are not proportional. / Bildbaserad modellering med visuella bilder har genomgått en stor utveckling under de tidigare delarna av 2000-talet. Givet en sekvens bestående av vanliga tvådimensionella bilder på en scen från olika perspektiv så är målet att rekonstruera en tredimensionell modell. I denna avhandling implementeras och testas ett system för automatiserad okalibrerad scenrekonstruktion från infraröda bilder. Okalibrerad rekonstruktion refererar till det faktum att parametrar för kameran, såsom fokallängd och fokus, är okända och enbart bilder används som indata till systemet. Ett stort användingsområde för värmekameror är inspektion. Temperaturskillnader i en bild kan indikera till exempel dålig isolering eller hög friktion. Om ett automatiserat system kan skapa en tredimensionell modell av en scen så kan det bidra till att förenkla inspektion samt till att ge en bättre överblick. Värmebilder kommer generellt att ha lägre upplösning, mindre kontrast och mindre högfrekvensinnehåll jämfört med visuella bilder. Dessa egenskaper hos infraröda bilder komplicerar extraktion och matchning av punkter i bilderna vilket är viktiga steg i rekonstruktionen. För att åtgärda komplikationen förbehandlas bilderna innan rekonstruktionen, ett urval av metoder för förbehandling har testats. Rekonstruktion med värmebilder kommer också att ställa ytterligare krav på rekonstruktionen, detta eftersom det är viktigt att bibehålla termisk noggrannhet från bilderna i modellen. Tre huvudresultat erhålls från denna avhandling. För det första är det möjligt att beräkna kamerakalibrering och position såväl som en gles rekonstruktion från en infraröd bildsekvens, detta med implementationen som föreslås i denna avhandling. För det andra presenteras och analyseras korrelationen för temperaturmätningar i bilderna som används för rekonstruktionen. Slutligen så visar den testade förbehandlingen inte en förbättring av rekonstruktionen som är propotionerlig med den ökade beräkningskomplexiteten.

When forensic examiners try to identify the perpetrator of a felony, they use individual facial marks when comparing the suspect with the perpetrator. Facial marks are often used for identification and they are nowadays found manually. To speed up this process, it is desired to detect interesting facial marks automatically. This master thesis describes a method to automatically detect and separate permanent and non-permanent marks. It uses a fast radial symmetry algorithm as a core element in the mark detector. After candidate skin mark extraction, the false detections are removed depending on their size, shape and number of hair pixels. The classification of the skin marks is done with a support vector machine and the different features are examined. The results show that the facial mark detector has a good recall while the precision is poor. The elimination methods of false detection were analysed as well as the different features for the classifier. One can conclude that the color of facial marks is more relevant than the structure when classifying them into permanent and non-permanent marks. / När forensiker försöker identifiera förövaren till ett brott använder de individuella ansiktsmärken när de jämför den misstänkta med förövaren. Dessa ansiktsmärken identifieras och lokaliseras oftast manuellt idag. För att effektivisera denna process, är det önskvärt att detektera ansiktsmärken automatiskt. I rapporten beskrivs en framtagen metod som möjliggör automatiskt detektion och separation av permanenta och icke-permanenta ansiktsmärken. Metoden som är framtagen använder en snabb radial symmetri algoritm som en huvuddel i detektorn. När kandidater av ansiktsmärken har tagits, elimineras alla falska detektioner utifrån deras storlek, form och hårinnehåll. Utifrån studiens resultat visar sig detektorn ha en god känslighet men dålig precision. Eliminationsmetoderna av falska detektioner analyserades och olika attribut användes till klassificeraren. I rapporten kan det fastställas att färgskiftningar på ansiktsmärkena har en större inverkan än formen när det gäller att sortera dem i permanenta och icke-permanenta märken.

Now and then train accidents occur. Collisions between trains and objects such as animals, humans, cars, and fallen trees can result in casualties, severe damage on the train, and delays in the train traffic. Thus, train collisions are a considerable problem with consequences affecting society substantially. The company Termisk Systemteknik AB has on commission by Rindi Solutions AB investigated the possibility to detect anomalies on the railway using a trainmounted thermal imaging camera. Rails are also detected in order to determine if an anomaly is on the rail or not. However, the rail detection method does not work satisfactory at long range. The purpose of this master’s thesis is to improve the previous rail detector at long range by using machine learning, and in particular deep learning and a convolutional neural network. Of interest is also to investigate if there are any advantages using cross-modal transfer learning. A labelled dataset for training and testing was produced manually. Also, a loss function tailored to the particular problem at hand was constructed. The loss function was used both for improving the system during training and evaluate the system’s performance during testing. Finally, eight different approaches were evaluated, each one resulting in a different rail detector. Several of the rail detectors, and in particular all the rail detectors using crossmodal transfer learning, perform better than the previous rail detector. Thus, the new rail detectors show great potential to the rail detection problem.

The recent emergence of time-of-flight cameras has opened up new possibilities in the world of computer vision. These compact sensors, capable of recording the depth of a scene in real-time, are very advantageous in many applications, such as scene or object reconstruction. This thesis first addresses the problem of fusing depth data with color images. A complete process to combine a time-of-flight camera with a color camera is described and its accuracy is evaluated. The results show that a satisfying precision is reached and that the step of calibration is very important. The second part of the work consists of applying super-resolution techniques to the time-of-flight camera in order to improve its low resolution. Different types of super-resolution algorithms exist but this thesis focuses on the combination of multiple shifted depth maps. The proposed framework is made of two steps: registration and reconstruction. Different methods for each step are tested and compared according to the improvements reached in term of level of details, sharpness and noise reduction. The results obtained show that Lucas-Kanade performs the best for the registration and that a non-uniform interpolation gives the best results in term of reconstruction. Finally, a few suggestions are made about future work and extensions for our solutions.

The objective of this master’s thesis work is to evaluate the potential benefit of a superpixel preprocessing step for general object detection in a traffic environment. The various effects of different superpixel parameters on object detection performance, as well as the benefit of including depth information when generating the superpixels are investigated. In this work, three superpixel algorithms are implemented and compared, including a proposal for an improved version of the popular Spectral Linear Iterative Clustering superpixel algorithm (SLIC). The proposed improved algorithm utilises a coarse-to-fine approach which outperforms the original SLIC for high-resolution images. An object detection algorithm is also implemented and evaluated. The algorithm makes use of depth information obtained by a stereo camera to extract superpixels corresponding to foreground objects in the image. Hierarchical clustering is then applied, with the segments formed by the clustered superpixels indicating potential objects in the input image. The object detection algorithm managed to detect on average 58% of the objects present in the chosen dataset. It performed especially well for detecting pedestrians or other objects close to the car. Altering the density distribution of the superpixels in the image yielded an increase in detection rate, and could be achieved both with or without utilising depth information. It was also shown that the use of superpixels greatly reduces the amount of computations needed for the algorithm, indicating that a real-time implementation is feasible.

Shape-Based matching (SBM) is a known method for 2D object recognition that is rather robust against illumination variations, noise, clutter and partial occlusion. The objects to be recognized can be translated, rotated and scaled. The translation of an object is determined by evaluating a similarity measure for all possible positions (similar to cross correlation). The similarity measure is based on dot products between normalized gradient directions in edges. Rotation and scale is determined by evaluating all possible combinations, spanning a huge search space. A resolution pyramid is used to form a heuristic for the search that then gains real-time performance. For SBM, a model consisting of normalized edge gradient directions, are constructed for all possible combinations of rotation and scale. We have avoided this by using (bilinear) interpolation in the search gradient map, which greatly reduces the amount of storage required. SBM is highly parallelizable by nature and with our suggested improvements it becomes much suited for running on a GPU. This have been implemented and tested, and the results clearly outperform those of our reference CPU implementation (with magnitudes of hundreds). It is also very scalable and easily benefits from future devices without effort. An extensive evaluation material and tools for evaluating object recognition algorithms have been developed and the implementation is evaluated and compared to two commercial 2D object recognition solutions. The results show that the method is very powerful when dealing with the distortions listed above and competes well with its opponents.

Abstract 3D visualization of geological structures is a very efficient way to create a good understanding of geological features. It is not only an illustrative way for common people, but also a comprehensive method to interpret results of the work. Geologists, geophysics engineers and GIS experts sometimes need to visualize an area to accomplish their researches. It can show how sample data are distributed over the area and therefore they can be applied as suitable approach to validate the result. Among different 3D modeling methods, some are expensive or complicated. Therefore, such a methodology enabling easy and cheap creation of a 3D construction is highly demanded. However, several obstacles have been faced during the process of constructing a 3D model of geology. The main debate over suitable interpolation methods is the fact that 3D modelers may face discrepancies leading to different results even when they are working with the same set of data. Furthermore, most often part of data can be source of errors, themselves. Hence, it is extremely important to decide whether to omit those data or adopt another strategy. However, even after considering all these points, still the work may not be accurate enough to be used for scientific researches if the interpretation of work is not done precisely. This research sought to explain an approach for 3D modeling of Sedini platform in Sardinia, Italy. GIS was used as a flexible software together with Surfer and Voxler. Data manipulation, geodatabase creation and interpolation test all have been done with aid of GIS. A variety of interpolation methods available in Surfer were used to opt suitable method together with Arc view. A solid 3D model is created in Voxler environment. In Voxler, in contrary to many other 3D types of software there are four components needed to construct 3D. C value as 4th component except for XYZ coordinates was used to differentiate special features in platform and do gridding based on chosen value. With the aid of C value, one can mark layer of interest to identify it from other layers. The final result shows a 3D solid model of the Sedini platform including both surfaces and subsurfaces. An Isosurface with its unique value (Isovalue) can mark layer of interest and make it easy to interpret the results. However, the errors in some parts of model are also noticeable. Since data acquisition was done for studying geology and mineralogy characteristics of the area, there is less number of data points collected per volume according to the main goals of the initial project. Moreover, in some parts of geological border lines, the density of sample points is not high enough to estimate accurate location of lines. The study result can be applicable in a broad range of geological studies. Resource evaluation, geomorphology, structural geology and GIS are only a few examples of its application. The results of the study can be compared to the results of similar works where different softwares have been used so as to comprehend pros and cons of each as well as appropriate application of each software for a special task.     Keywords: GIS, Image Interpretation, Geodatabase, Geology, Interpolation, 3D Modeling

Just how far is it possible to make learning of new parts for recognition and robot picking autonomous? This thesis initially gives the prerequisites for the steps in learning and calibration that are to be automated. Among these tasks are to select a suitable part model from numerous candidates with the help of a new part segmenter, as well as computing the spatial extent of this part, facilitating robotic collision handling. Other tasks are to analyze the part model in order to highlight correct and suitable edge segments for increasing pattern matching certainty, and to choose appropriate acceptance levels for pattern matching. Furthermore, tasks deal with simplifying camera calibration by analyzing the calibration pattern, as well as compensating for differences in perspective at great depth variations, by calculating the centre of perspective of the image. The image processing algorithms created in order to solve the tasks are described and evaluated thoroughly. This thesis shows that simplification of steps of learning and calibration, by the help of advanced image processing, really is possible.

The purpose of this thesis is to develop an application for mobile phones that simplifies communication. The company Doberman wanted to look at possibilities to develop such an application that uses Bluetooth™ technol-ogy to communicate in ad-hoc networks. The aim has been an application to run on mobile phones in which you can send messages and files to other devices and also add a user profile with personal information to share with others. The communication will take place in temporary networks created when Bluetooth enabled devices is in range of each other. The market for mobile phones has grown rapidly over the past years and is still growing. There are many differ-ent phone models and it is difficult to find a developer platform that covers many phone models. In the beginning of this thesis an inquiry of different developer platforms has been made. The Java™ platform is supported by most phones but has limitations in accessing functions on the device. The best alternative was Symbian C++ for devices with Symbian OS. This alternative does not have the same limitations as Java and is still supported by relatively many devices. The application was then developed in Symbian C++. There are a number of different versions of Symbian OS and different GUI-platforms that runs on Symbian OS which leads to other issues in the development. We have limited the development of the application to the Series 60 platform for Symbian OS v7.0s. During design and implementation portability to other GUI-platforms has been considered. We have tested the application on emulator compatible with Symbian OS v7.0s and Symbian OS v8.0a and found some compatibility problems between the two versions. We have also tested the application on mobile phones and between emulator and the phone with corresponding OS-version no new problems occurred