<p>Segmentation is a process that separates objects in an image. In medical images, particularly image volumes, the field of application is wide. For example 3D visualisations of the anatomy could benefit enormously from segmentation. The aim of this thesis is to construct a segmentation tool.</p><p>The project consist three main parts. First, a survey of the actual need of segmentation in medical image volumes was carried out. Then a unique three-step model for a segmentation tool was implemented, tested and evaluated.</p><p>The first step of the segmentation tool is a seed-growing method that uses the intensity and an orientation tensor estimate to decide which voxels that are part of the project. The second step uses an active contour, a deformable “balloon”. The contour is shrunk to fit the segmented border from the first step, yielding a surface suitable for visualisation. The last step consists of letting the contour reshape according to the orientation tensor estimate.</p><p>The use evaluation establishes the usefulness of the tool. The model is flexible and well adapted to the users’ requests. For unclear objects the segmentation may fail, but the cause is mostly poor image quality. Even though much work remains to be done on the second and third part of the tool, the results are most promising.</p>

<p>Automated storage systems often rely on that the positions of the pallets are known with high precision. In this thesis, a turnable camera mounted on the robot has been used for handling the situation of approximately known pallet positions. The robot is given the approximate location of a pallet, and its objective is to locate the pallet with a precision that is high enough to be able to approach it from the correct direction and then lift it. For this, a precision of a few centimetres in each direction is needed.</p><p>A system for locating the pallet from single images, based on rotational symmetry filters, has been developed, and a simple program for controlling the robot has been implemented. These could very well be extended and improved, e.g. by considering multiple images and improving the path planning.</p><p>The main part of the thesis deals with the image processing part. Other parts of the project, apart from the controller, include implementation of servers controlling the camera and the frame grabber.</p><p>Some tests have been made, which show fairly promising results.</p>

<p>This thesis investigates the possibilities of using GIS (Geographic Information System) data with an airborne autonomous vehicle developed in the WITAS project. Available for the thesis are high resolution (0.16 meter sample interval) aerial photographs over Stockholm, and vector data in a common GIS format containing all roads in the Stockholm area.</p><p>A method for removing cars from aerial photographs is presented, using the filtering method normalized convolution, originally developed for filtering uncertain and incomplete data. By setting the certainty to zero over the cars, this data is disregarded in the filtering process, resulting in an image without cars. This method is further improved by choosing an anisotropic applicability function, resulting in a filtering that preserves structures oriented in certain directions.</p><p>The available vector data is investigated with regard to its use in a simulator for vehicle movement, and is found to be missing much of the essential information needed in such a simulator. A new data format better suited to these requirements is created, using the extensible markup language (XML) which generates a humanreadable data format and can use existing parsers to make the implementation simpler. The result is a somewhat complex, but highly general data format that can accurately express almost any type of road and intersection. Cars can follow arbitrary paths in the road database and move with a smooth motion suitable for use as input to image processing equipment. The simulator does not allow any dynamic behaviour such as changing speeds, starting or stopping, or interaction between cars, takeovers or intelligent behavior in intersections.</p><p>In the airborne vehicle, a mapping from pixels in a camera image (like the ones output from the simulator) to locations in the road database is needed. This is an inverse mapping with respect to visualizing as described above. This gives important information to a car tracking system regarding the probable movement of cars and also making it possible to determine if a car breaks traffic regulations. A mapping of this kind is created using a simplified form of ray tracing known as ray casting, together with space partitioning methods used to vastly improve efficiency.</p><p>All above mentioned tasks are implemented using C++ and object oriented methods, giving maintainable and extendable code suiting a quickly changing research area. The interface to the simulator is designed to be compatible to the existing simulation software used in the WITAS project. Visualization is done through the OpenGL graphics library, providing realistic effects such as lighting and shading.</p>

<p>We explore the use of colour for interpretation of unstructured off-road scenes. The aim is to extract driveable areas for use in an autonomous off-road vehicle in real-time. The terrain is an unstructured tropical jungle area with vegetation, water and red mud roads.</p><p>We show that hue is both robust to changing lighting conditions and an important feature for correctly interpreting this type of scene. We believe that our method also can be deployed in other types of terrain, with minor changes, as long as the terrain is coloured and well saturated.</p><p>Only 2D information is processed at the moment, but we aim at extending the method to also treat 3D information, by the use of stereo vision or motion.</p>

<p>This Master's Thesis discusses the different trade-offs a programmer needs to consider when constructing image processing systems. First, an overview of the different alternatives available is given followed by a focus on systems based on general hardware. General, in this case, means mass-market with a low price-performance-ratio. The software environment is focused on UNIX, sometimes restricted to Linux, together with C, C++ and ANSI-standardized APIs.</p>

<p>The aim of this master thesis is to classify the tree class from an image of a leaf with a computer vision classiffication system. We compare different descriptors that will describe the leaves different features. We will also look at different classiffication models and combine them with the descriptors to build a system hat could classify the different tree classes.</p>

<p>IT systems rely on correct authentication of their users in order to provide confidentiality and integrity of data. When accessing systems remotely, for instance over the Internet, no assumptions can be made regarding the level of security on the computer used. Such computers may be exposed to malware, keyloggers and other threats and must therefore generally be considered as untrusted.</p><p>To increase security when users connect remotely from untrusted clients various authentication mechanisms can be used. Usability must however be considered when deploying new mechanisms. Protection must also be balanced to the load put on users.</p><p>This thesis gives a presentation of common authentication mechanisms available and enumerates the main attack vectors threatening correct authentication and credentials. Furthermore a ranking method is proposed in order to evaluate authentication mechanisms in relation to each other.</p><p>Using the outcome of the ranking of existing methods an authentication system called Smokey (Synchronizable Mobile Key) is proposed and implemented. Smokey uses Java capable cell phones as hardware tokens generating short time valid one time passwords. Whereas traditional tokens may cease to work under certain circumstances Smokey provides users the ability to synchronize with the authentication server aiming for high usability.</p>

<p>This thesis presents a new method for detection of complex curvatures such as corners, circles, and star patterns. The method is based on a second degree local polynomial model applied to a local orientation description in double angle representation. The theory of rotational symmetries is used to compute curvature responses from the parameters of the polynomial model. The responses are made more selective using a scheme of inhibition between different symmetry models. These symmetries can serve as feature points at a high abstraction level for use in hierarchical matching structures for 3D estimation, object recognition, image database search, etc.</p><p>A very efficient approximative algorithm for single and multiscale polynomial expansion is developed, which is used for detection of the complex curvatures in one or several scales. The algorithm is based on the simple observation that polynomial functions multiplied with a Gaussian function can be described in terms of partial derivatives of the Gaussian. The approximative polynomial expansion algorithm is evaluated in an experiment to estimate local orientation on 3D data, and the performance is comparable to previously tested algorithms which are more computationally expensive.</p><p>The curvature algorithm is demonstrated on natural images and in an object recognition experiment. Phase histograms based on the curvature features are developed and shown to be useful as an alternative compact image representation.</p><p>The importance of curvature is furthermore motivated by reviewing examples from biological and perceptual studies. The usefulness of local orientation information to detect curvature is also motivated by an experiment about learning a corner detector.</p>

<p>The need for wireless communications has increased during the last decades. To increase the data rates of the communication links there is a need of allocating larger frequency bands. These bands are strictly regulated and the majority of the frequencies are allocated to licensed systems. The splitting of the bandwidth is orthogonal, which mean that the different systems are not interfering each other. But, orthogonal splitting is inefficient since it does not exploit all degrees of freedom in the wireless channels.</p><p>There are also unlicensed bands where different systems co-exist and operate simultaneously in a non-orthogonal manner and interfere each other. This interference degrades the performance of each system. This motivates the use of so-called spectrum sharing techniques for interference management.</p><p>The spectrum sharing can be modeled via the so-called interference channel (IFC). This consists of at least two transmitter (TX)-receiver (RX) pairs. These pairs can share resources such as frequency, time, power, code, or space. Here, the focus is on the sharing of spatial resources. By employing multiple antennas at the TXs, spatial diversity is obtained and it is possible to steer the power in any spatial direction. Assuming a single antenna at each RX we get the so-called multiple-input single-output (MISO) IFC.</p><p>There is a conflict inherent in the IFC since the TX-RX pairs optimize conflicting objectives, e.g., the data rates. To analyze this conflict we use game-theoretic concepts. In general, the situation where the TXs transmit in the directions which are optimal for their objective is inefficient. That is, it is possible increase all rates of some (or all) TX-RX pairs without decreasing the rate of any of the pairs. To do so, the TXs change their strategies such that interference is decreased.</p><p>We define several rate regions, which depend on the channel model and channelstate information at the transmitters. Also, some of the most important game-theoretic operating points are described.</p>

<p>Around the world, vehicle emission regulations become stricter, increasing exhaust emission demands. To manage these rules and regulations, vehicle manufacturers put a lot of effort into minimizing the exhaust emissions. The three-way catalytic converter was developed, and today it is the most commonly used device to control the exhaust emissions.</p><p>To work properly the catalytic converter needs to control the air-fuel mixture with great precision. This then increases the demands on the engine management systems, causing them to become more complex. With increased complexity, the time effort of optimizing parameters has grown drastically, hence increasing development costs. In addition to this, operating conditions change due to vehicles age, requiring further optimization of the parameters while running.</p><p>To minimize development cost and to control the air-fuel mixture with great precision during an engines full life span, this master thesis proposes a self-optimized system, i.e. an adaptive system, to control the air-fuel mixture.</p><p>In the suggested method, the fuel injection to the engine is controlled with help of a linear lambda sensor, which measures the air-fuel mixture. The mapping from injection to measured air-fuel mixture forms a nonlinear system. It can be approximated as a linear function at static engine operating points, allowing the system at each static point to be modelled as a first order system with long time delay. To enable utilization over full operating area, and not only in static point, the controller uses large maps, so called gain-scheduling maps, to change control parameters.</p><p>The tested controller is model based. It uses an Otto-Smith Predictor and a feed forward connection of target air-fuel. The model parameters in the controller are updated while driving and the adaptation method used is based on a least squares algorithm.</p><p>The performance of the adapted controller and the adaptation method is tested in both simulation environment and in vehicle, showing good potential.</p>