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Master theses

  1. Visualization of Military Camp Sites
    Student: Fredrik Olsson
    Supervisors: Björn Brundin
    Subject supervisor: Ingela Nyström
    Publisher: CBA Master Thesis No. 114 / UPTEC F10 022
    Comment: Only available from SAAB Aerotech
    Abstract: The purpose with this Master thesis project was to develop a tool, where 3D objects that can be found in military camps are created. These objects should be assembled to a 3D model of a camp. A prototype has been implemented that can be used for evaluation of how useful a 3D visualization of a military camp is and what benefits it can obtain compared to a 2D sketch. The 3D visualizations are created in SketchUp and functionality is in priority in front of graphical details. In addition, SketchUp is used as a tool when planning new military camps, so it is necessary that all objects can be deleted and moved and it should also be possible to add new objects to the camp. A Matlab function was written to read 2D maps and project them to a 3D map so the terrain can be imported to the SketchUp model. One prerequisite of the project is that the program should work on a quite ordinary laptop. Hence, in order to save memory space and computational times, the objects created are as small as possible (regarding bytes), without losing too much detail. A number of example camps are shown with various objects such as tents, vehicles, and roads.

  2. Synthetic 3D Pap Smear Nucleus Generation
    Student: Sandra Gomez
    Supervisor: Patrik Malm
    Subject supervisor: Patrik Malm
    Publisher: CBA Master Thesis No. 115
    Abstract: In this project we present a 3D Pap smear cell nucleus generator. The shape and the texture are the important features for a realistic synthetic nucleus. For the first one, the shape, a deformed distance transform is used in order to generate deformed spheres. For the second one, the texture, a pseudo random noise algorithm, Perlin noise, is applied to the shape in order to generate the most realistic texture of a cell. As a result, we obtain synthetic 3D cell nuclei as they appear in Pap smear tests.

  3. Vad är viktigast i staden?
    Student: Erik Almlöf
    Supervisors: Mats Dunkars
    Subject supervisor: Ewert Bentsson
    Publisher: CBA Master Thesis No. 116 / UPTEC STS 10 026
    Abstract: This paper is part of the research programme ViSuCity, a programme with the goal of creating more sustainable urban planning through the development of better visual tools, which ultimately means better communication between various parties of public planning. The paper concerns the implementation of MCE into a 3D program for visualization. Multi criteria evaluation (MCE) is a technique that has been developed during the last 20 years. It merges GIS with AHP, forming a decision making tool for localization of, for example, new buildings. The result is an automated tool that enables advanced analysis of geographic areas. The tool has a very high potential due to the completely automated MCE and it is adapted for people without a technical background, let alone formal training in MCE. It provides great opportunities to test different scenarios, something that should be an important advantage. The incorporation of MCE into 3D models has made it easier for users to relate the maps to reality, since a detailed 3D model is very easily understood in terms of geographical placement. A brand new feature that has not previously been used is the ability to import new objects and give feedback to the analysis. A summary of research on the MCE underlines the current situation, that relatively little research exists surrounding the use and demand of MCE. This paper unfortunately contributes to this fact since no user studies have been done due to lack of time. This is something future research should focus on.

  4. Nuclei Segmentation on Bright-Field Images
    Student: Fernandez, Francisco Cruz
    Supervisor: Amin Allalou
    Subject supervisor: Amin Allalou
    Publisher: CBA Master Thesis No. 117/UPTEC IT 10 027
    Abstract: Nuclei segmentation is a common and complicated task in image analysis. There is no general solution for the problem, and depending on the image characteristics the segmentation can be performed in different ways. Bright-field images add some complications to the problem; the color of some elements of the image is close to the color of the nuclei, making the segmentation difficult. In this thesis some methods are presented to complete this task, two classifiers, minimum distance classifier and multilayer perception are tested to enhance the nuclei. After the classification, threshold methods together with morphological operations are used to get the segmentation of the nuclei with an accuracy around 85%.

  5. Implementation of 3D Imaging for Two-photon Laser Scanning Microscopy
    Student: Chetan Nagaraja
    Supervisor: Klas Kullander, Dept. of Neuroscience, UU
    Subject supervisor: Robin Strand
    Publisher: CBA Master Thesis No. 118 / UPTEC IT 10 031
    Abstract: Information exchange between neural systems occurs at the level of populations of neurons. Thus in order to understand how this information exchange occurs, it is indispensable to understand the role of underlying neuronal systems.

    Electrophysiological techniques have enhanced our understanding of the nervous system by enabling the study of properties of single ion channels to that of ensembles of neurons. While electrophysiological measurements offer excellent temporal resolution, high sensitivity and a good SNR as they are in direct physical contact with the cells under study, they lack spatial resolution as this method provides a readout of the electrical signals from single or ensembles of neurons in the vicinity of the electrodes (Scanziani et al, 2009).

    Imaging techniques have gained a lot of prominence because they are non-invasive and provides excellent spatial resolution (Scanziani et al, 2009). The advent of fluorescent genetically encoded optical probes and other fluorescent synthetic indicators has enabled the study of network functions of neurons (Handel et al, 2008).

    There are various imaging techniques but the one most suited to study network activity is Multiphoton emission (MPE) microscopy because of its ability to image at greater depths in the tissue. In particular, the most popular and extensively used method in this class is the 2-Photon Microscopy. This has provided the ability to study activity patterns of neuronal ensembles at greater depths and the phototoxicity associated with one photon emission is greatly reduced (Potter, 1996).

    Imaging methods until recently have employed 2D scanning at planes normal to the light axis. It is known that processing of information occurs at local ensembles of neurons , hence obtaining population activity in a volume of interest is of greater relevance. This has been possible with the technological advancements over the past couple of years (Gobel et al, 2007).

    The aim of this thesis is to implement a fast 3D scanning algorithm using 2-photon microscopy to measure the activity patterns of neuronal ensembles. Further, this technique could be used in order to relate the activity of neurons with the behavioral output.

  6. Analysis Application for H.264 Video Encoding
    Student: Ying Wang
    Supervisors: Zhuangfei Wu and Clinton Priddle
    Subject supervisor: Cris Luengo
    Publisher: CBA Master Thesis No. 119 / UPTEC IT 10 061
    Abstract: A video analysis application ERANA264(Ericsson Research h.264 video ANalysis Application) is developed in this project. Erana264 is a tool that analyzes H.264 encoded video bitstreams, extracts the encoding information and parameters, analyzes them in different stages and displays the results in a user friendly way. The intention is that such an application would be used during development and testing of video codecs. The work is implemented on top of existing H.264 encoder/decoder source code (C/C++) developed at Ericsson Research.
    Erana264 consists of three layers. The first layer is the H.264 decoder previously developed in Ericsson Research. By using the decoder APIs, the information is extracted from the bitstream and is sent to the higher layers. The second layer visualizes the different decoding stages, uses overlay to display some macro block and picture level information and provides a set of play back functions. The third layer analyzes and presents the statistics of prominent parameters in video compression process, such as video quality measurements, motion vector distribution, picture bit distribution etc.

  7. Underwater 3D Surface Scanning using Structured Light
    Student: Nils Törnblom
    Supervisor: David Stenman, WesDyne TRC AB, Täby
    Subject supervisor: Cris Luengo
    Publisher: CBA Master Thesis No. 120 / UPTEC F 10 063
    Abstract: In this thesis project, an underwater 3D scanner based on structured light has been constructed and developed. Two other scanners, based on stereoscopy and a line-swept laser, were also tested. The target application is to examine objects inside the water filled reactor vessel of nuclear power plants. Structured light systems (SLS) use a projector to illuminate the surface of the scanned object, and a camera to capture the surfaces' reflection. By projecting a series of specific line-patterns, the pixel columns of the digital projector can be identified off the scanned surface. 3D points can then be triangulated using ray-plane intersection. These points form the basis the final 3D model.
    To construct an accurate 3D model of the scanned surface, both the projector and the camera need to be calibrated. In the implemented 3D scanner, this was done using the Camera Calibration Toolbox for Matlab. The codebase of this scanner comes from the Matlab implementation by Lanman & Taubin at Brown University. The code has been modified and extended to meet the needs of this project. An examination of the effects of the underwater environment has been performed, both theoretically and experimentally. The performance of the scanner has been analyzed, and different 3D model visualization methods have been tested.
    In the constructed scanner, a small pico projector was used together with a high pixel count DSLR camera. Because these are both consumer level products, the cost of this system is just a fraction of commercial counterparts, which uses professional components. Yet, thanks to the use of a high pixel count camera, the measurement resolution of the scanner is comparable to the high-end of industrial structured light scanners.

  8. Evaluation of a Holographic 3D Display
    Student: Jim Björk
    Supervisors: Robin Strand, Ingrid Carlbom
    Subject supervisor: Stefan Seipel
    Publisher: CBA Master Thesis No. 121 / UPTEC F 10 064
    Abstract: An autostereoscopic display based on a Holographic Optical Element (HOE) presents new opportunities for faithful 3D displaying but also presents potential new problems, such as: accuracy of 3D objects, interactivity and user perception. In this evaluation, which is the first of its kind for this type of display, I have explored and tested methods and tools for the evaluation of these potential problems. I have found that the visual quality is comparable to more common display types but with a significant visual delay due to the parallel rendering of graphics and the projectors significant input lag. From this I have concluded that the display system is not yet ready for its intended purpose, cranio-maxillofacial surgery planning. We need projectors with less input lag and preferably better optics. The software needs to be optimized for multimonitor rendering as well.

  9. Gait-based Reidentification of People in Urban Surveillance Video
    Student: Daniel Skog
    Supervisor: Cris Luengo
    Subject supervisor: Robin Strand
    Publisher: CBA Master Thesis No. 122 / UPTEC IT 10 040
    Abstract: Video surveillance of large urban areas demands the use of multiple cameras. consider tracking a person moving between cameras in such a system. When the person disappears from the view of one camera and then reappears in another, the surveillance system should be able to determine that the person has been seen before and continue tracking. The process of determining this connection is known as reidentification.

    Gait is a biometric that has been shown to be useful in determining the identities of people. It is also useful for reidentification as it is not affected by varying lighting conditions between cameras. Also, it is hard for people to alter the way they are walking without it looking unnatural.

    This project explores how gait can be used for reidentification. To investigate this, a number of different gait-based methods used for identification of people were used for reidentification. The methods are based on the active energy image, gait energy image, frame difference energy image, contours of silhouettes, and the self-similarity plot. The Fourier transform of the gait silhouette volume will also be tested. These methods are appearance based and the common theme is that a sequence of silhouettes of the subject is transformed into a representation of the gait. The representations are then used for reidentification by comparing them to other gaits in a pool using a simple classification method based on the nearest neighbor classifier.

    Two datasets were used to test the methods. The first dataset was captured with live surveillance cameras in an urban scene and the second using a home video camera. The lower quality of the footage in the first dataset affected the results, obtaining only about 34% correct reidentifications. This can be compared with the higher quality dataset which gave a result of about 80% correct reidentifications.

  10. Image Processing to Detect Worms 
    Student: Javier Fernández 
    Supervisor: Johan Henriksson (KI)
    Subject supervisor: Anders Brun
    Examiner: Anders Jansson 
    Partner: Karolinska Institutet 
    Publisher: CBA Master Thesis No. 123 / UPTEC IT 10 045 
    Abstract: The nematode C. elegans is a widely used model organism. It has many cells with human equivalents, making it possible to study pathways conserved in humans and related conditions. Being small and transparent, it also lends itself well to a variety of high-throughput screening techniques. Worm identification should be as automated as possible since it is too labor-intense and time-consuming to do it manually.

    Here we present an image processing methodology to detect C. elegans in high-throughput microscope images. The provided semi-automatic solution makes it possible to effectively identify individual worms in worm clusters. In general terms, the process is as follows: A given image is segmented, thus separating groups of worms from the background. Individual worms are detected automatically, following a worm-shape matching process. For worm clusters, the matching process is based on finding feasible worm shapes by minimizing the distance between the cluster and generic worm shapes, which are deformed to fit it. Wrong and missing conformations can be quickly fixed manually.

    The provided methodology is a novel approach to successfully detect individual C. elegans worms in high-throughput microscope images. Results show that this semi-automatic solution makes it possible to fit the shape of 100% of worms in the image, unlike previous automated methods that reach, at most, less than 90% in average, for similar test sets. The detection process is usually achieved in less than half a minute for difficult images. For easier images, the total match can often be calculated in a fully automatic way. Time cost and matching accuracy are considerably improved with respect to manual identification.

    The solution was implemented in Java and adjusted to Endrov, which is an open source plug-in architecture for image analysis, and is to be used at the Dept. of Bioscience and Nutrition, Karolinska Institute, Sweden.

  11. Digital Straight Line Segment Recognition on Non-Standard Point Lattices
    Student: Kelly Hubble
    Supervisor: Robin Strand
    Subject supervisor: Andreas Strömbergsson, Dept. of Mathematics, UU
    Publisher: U.U.D.M. project report; 2010:1
    Abstract: OC-DSSr is a digital straight line segment (DSS) recognition method in 3D non-Cartesian point lattices. A brief overview of image analysis is given, along with its relationship to digital geometry and non-Cartesian cubic lattices. The Body-Centered Cubic (BCC) and Face-Centered Cubic (FCC) lattices are reviewed. A digitization method-dependent definition of a DSS is used to develop OC-DSSr. The supercover digitization is used to digitize curves on non-Cartesian lattices. An extension to the supercover is proposed to achieve -connectivity in non-Cartesian lattices. A new independent definition of a DSS is proposed, based on the presented recognition method.

  12. Development of an Image Processing Tool for Fluorescence Microscopy Analysis of Paper Chemistry 
    Student: Åsa Nyflött 
    Supervisor: Lars Johansson, Karlstad University, Gunilla Carlsson, Karlstad University, Carl-Henrik Ljungqvist, Stora Enso, Anders Brun
    Examiner: Kjell Magnusson, Karlstad University 
    Partners: Karlstads Universitet, Stora Enso 
    Publisher: Karlstads Universitet 
    Abstract: Paper making today is, to some extent, based on empirical knowledge. It is well known that fines, pH, charge and ion strength affect the manufacture of paper. One way of extending knowledge of the mechanisms of paper chemistry is to follow the trajectories of fines and additives in the paper suspension to gather information as to the manner in which they react. Four tracking algorithms adapted to the needs of this particular problem were implemented in order to track particles efficiently. The tracking algorithms include two variants of the well-known Lucas-Kanade algorithm and template matching techniques based on cross-correlation and least squares matching. Although these techniques are similar in principle, the actual tracking can nevertheless differ; the Lucas-Kanade algorithms were found to be more invariant to noise, whereas the cross- correlation and least squares methods are more rapid to execute in Matlab. The tracking methods have been evaluated using a simulator to generate image sequences of synthetic particles moving according to Brownian motion. Tracking has also been evaluated on microscope images of real latex particles where the results have been compared to manual tracking. Tracking of both the simulated particles and the latex particles resulted in similar results when compared to known position and manual tracking, respectively.

    The developed simulator was used to evaluate the tracking algorithms and it can also be used to predict a real system if it can be expressed mathematically.

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