- 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.
- 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.
- 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.
- 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%.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
