<p>Time of flight is an imaging technique with uses depth information to capture 3D information in a scene. Recent developments in the technology have made ToF cameras more widely available and practical to work with. The cameras now enable real time 3D imaging and positioning in a compact unit, making the technology suitable for variety of object recognition tasks</p><p>An object recognition system for locating teats is at the center of the DeLaval VMS, which is a fully automated system for milking cows. By implementing ToF technology as part of the visual detection procedure, it would be possible to locate and track all four teat’s positions in real time and potentially provide an improvement compared with the current system.</p><p>The developed algorithm for teat detection is able to locate teat shaped objects in scenes and extract information of their position, width and orientation. These parameters are determined with an accuracy of millimeters. The algorithm also shows promising results when tested on real cows. Although detecting many false positives the algorithm was able to correctly detected 171 out of 232 visible teats in a test set of real cow images. This result is a satisfying proof of concept and shows the potential of ToF technology in the field of automated milking.</p>

<p>RED Digital Cinema is a rather new company that has developed a camera that has shaken the world of the film industry, the RED One camera. RED One is a digital cinema camera with the characteristics of a 35mm film camera. With a custom made 12 megapixel CMOS sensor it offers images with a filmic look that cannot be achieved with many other digital cinema cameras.</p><p>With a new camera comes a new set of media files to work with, which brings new software applications supporting them. RED Digital Cinema has developed several applications of their own, but there are also a few other software supporting RED. However, as of today the way of working with the RED media files together with these software applications are yet in progress.</p><p>During the short amount of time that RED One has existed, many questions has risen about what workflow is the best to use. This thesis presents a theoretical background of the RED camera and some software applications supporting RED media files. The main objective is to analyze RED material as well as existing workflows and find the optimal option.</p>

<p>The purpose of this master thesis, performed at FOI, was to evaluate a range gated underwater camera, for the application identification of bottom objects. The master thesis was supported by FMV within the framework of “arbetsorder Systemstöd minjakt (Jan Andersson, KC Vapen)”. The central part has been field trials, which have been performed in both turbid and clear water. Conclusions about the performance of the camera system have been done, based on resolution and contrast measurements during the field trials. Laboratory testing has also been done to measure system specific parameters, such as the effective gate profile and camera gate distances.</p><p>The field trials shows that images can be acquired at significantly longer distances with the tested gated camera, compared to a conventional video camera. The distance where the target can be detected is increased by a factor of 2. For images suitable for mine identification, the increase is about 1.3. However, studies of the performance of other range gated systems shows that the increase in range for mine identification can be about 1.6. Gated viewing has also been compared to other technical solutions for underwater imaging.</p>

<p>Detta examensarbete utreder avståndsbedömning med hjälp av bildbehandling och stereoseende för känd kamerauppställning.</p><p>Idag existerar ett stort antal beräkningsmetoder för att få ut avstånd till objekt, men metodernas prestanda har knappt mätts. Detta arbete tittar huvudsakligen på olika blockbaserade metoder för avståndsbedömning och tittar på möjligheter samt begränsningar då man använder sig av känd kunskap inom bildbehandling och stereoseende för avståndsbedömning. Arbetet är gjort på Bofors Defence AB i Karlskoga, Sverige, i syfte att slutligen användas i ett optiskt sensorsystem. Arbetet utreder beprövade</p><p>Resultaten pekar mot att det är svårt att bestämma en närmask, avstånd till samtliga synliga objekt, men de testade metoderna bör ändå kunna användas punktvis för att beräkna avstånd. Den bästa metoden bygger på att man beräknar minsta absolutfelet och enbart behåller de säkraste värdena.</p>

<p>This thesis describes and evaluates a number of approaches and algorithms for nonuniform correction (NUC) and suppression of fixed pattern noise in a image sequence. The main task for this thesis work was to create a general NUC for infrared focal plane arrays. To create a radiometrically correct NUC, reference based methods using polynomial approximation are used instead of the more common scene based methods which creates a cosmetic NUC.</p><p>The pixels that can not be adjusted to give a correct value for the incomming radiation are defined as dead. Four separate methods of identifying dead pixels are used to find these pixels. Both the scene sequence and calibration data are used in these identifying methods.</p><p>The algorithms and methods have all been tested by using real image sequences. A graphical user interface using the presented algorithms has been created in Matlab to simplify the correction of image sequences. An implementation to convert the corrected values from the images to radiance and temperature is also performed.</p>

<p>Foreground segmentation is a common first step in tracking and surveillance applications.  The purpose of foreground segmentation is to provide later stages of image processing with an indication of where interesting data can be found.  This thesis is an investigation of how foreground segmentation can be performed in two contexts: as a pre-step to trajectory tracking and as a pre-step in indoor surveillance applications.</p><p>Three methods are selected and detailed: a single Gaussian method, a Gaussian mixture model method, and a codebook method.  Experiments are then performed on typical input video using the methods.  It is concluded that the Gaussian mixture model produces the output which yields the best trajectories when used as input to the trajectory tracker.  An extension is proposed to the Gaussian mixture model which reduces shadow, improving the performance of foreground segmentation in the surveillance context.</p>

<p>En modern grafikprocessor är oerhört kraftfull och har en prestanda som potentiellt sett är många gånger högre än för en modern mikroprocessor. I takt med att grafikprocessorn blivit alltmer programmerbar har det blivit möjligt att använda den för beräkningstunga tillämpningar utanför dess normala användningsområde. Inom det här arbetet utreds vilka möjligheter och begränsningar som uppstår vid användandet av grafikprocessorer för generell programmering. Arbetet inriktas främst mot signal- och bildbehandlingstillämpningar men mycket av principerna är tillämpliga även inom andra områden.</p><p>Ett ramverk för bildbehandling implementeras och några algoritmer inom bildanalys realiseras och utvärderas, bland annat stereoseende och beräkning av optiskt flöde. Resultaten visar på att vissa tillämpningar kan uppvisa en avsevärd prestandaökning i en grafikprocessor jämfört med i en mikroprocessor men att andra tillämpningar kan vara ineffektiva eller mycket svåra att implementera.</p> / <p>The modern graphical processing unit, GPU, is an extremely powerful unit, potentially many times more powerful than a modern microprocessor. Due to its increasing programmability it has recently become possible to use it in computation intensive applications outside its normal usage. This work investigates the possibilities and limitations of general purpose programming on GPUs. The work mainly concentrates on signal and image processing although much of the principles are applicable to other areas as well.</p><p>A framework for image processing on GPUs is implemented and a few computer vision algorithms are implemented and evaluated, among them stereo vision and optical flow. The results show that some applications can gain a substantial speedup when implemented correctly in the GPU but others can be inefficent or extremly hard to implement.</p>

<p>Image segmentation is the problem of partitioning an image into meaningful parts, often consisting of an object and background. As an important part of many imaging applications, e.g. face recognition, tracking of moving cars and people etc, it is of general interest to design robust and fast segmentation algorithms. However, it is well accepted that there is no general method for solving all segmentation problems. Instead, the algorithms have to be highly adapted to the application in order to achieve good performance. In this thesis, we will study segmentation methods for blood vessels in medical images. The need for accurate segmentation tools in medical applications is driven by the increased capacity of the imaging devices. Common modalities such as CT and MRI generate images which simply cannot be examined manually, due to high resolutions and a large number of image slices. Furthermore, it is very difficult to visualize complex structures in three-dimensional image volumes without cutting away large portions of, perhaps important, data. Tools, such as segmentation, can aid the medical staff in browsing through such large images by highlighting objects of particular importance. In addition, segmentation in particular can output models of organs, tumors, and other structures for further analysis, quantification or simulation.</p><p>We have divided the segmentation of blood vessels into two parts. First, we model the vessels as a collection of lines and edges (linear structures) and use filtering techniques to detect such structures in an image. Second, the output from this filtering is used as input for segmentation tools. Our contributions mainly lie in the design of a multi-scale filtering and integration scheme for de- tecting vessels of varying widths and the modification of optimization schemes for finding better segmentations than traditional methods do. We validate our ideas on synthetical images mimicking typical blood vessel structures, and show proof-of-concept results on real medical images.</p>

<p>The WinCandide application, a platform for face tracking and model based coding, had become out of date and needed to be upgraded. This report is based on the work of investigating possible open source GUIs and computer vision tool kits that could replace the old ones that are unsupported. Multi platform GUIs are of special interest.</p>

<p>With numerous applications in both military and civilian life, the demand for accurate 3D models of real world environments increases rapidly. Using an airborne laser scanner for the raw data acquisition and robust methods for data processing, the researchers at the Swedish Defence Research Agency (FOI) in Linköping hope to fully automate the modeling process.</p><p>The work of this thesis has mainly been focused on three areas: ground estimation, image segmentation and classification. Procedures have in each of these areas been developed, leading to a new algorithm for ground estimation, a number of segmentation methods as well as a full comparison of various decision values for an object based classification. The ground estimation algorithm developed has yielded good results compared to the method based on active contours previously elaborated at FOI. The computational effort needed by the new method has been greatly reduced compared to the former, as performance, particularly in urban areas, has been improved. The segmentation methods introduced have shown promising results in separating different types of objects. A new set of decision values and descriptors for the object based classifier has been suggested, which, according to tests, prove to be more efficient than the set p reviously used.</p> / <p>Med många tillämpningar både inom det civila och militära, ökar efterfrågan på noggranna och korrekta omvärldesmodeller snabbt. Forskare på FOI, Totalförsvarets Forskningsinstitut, arbetar med att fullt ut kunna automatisera den process som genererar dessa tredimensionella modeller av verkliga miljöer. En luftburen laserradar används för datainsamlingen och robusta metoder är under ständig utveckling för den efterföljande databehandlingen.</p><p>Arbetet som presenteras i denna rapport kan delas in i tre huvudområden: skattning av markyta, segmentering av data samt klassificering. Metoder inom varje område har utvecklats vilket lett fram till en ny algoritm för markestimering, en rad metoder för segmentering samt en noggrann jämförelse av olika beslutsvärden för en objektbaserad klassificering. Markskattningsalgoritmen har visat sig vara effektiv i jämförelse med en metod baserad på aktiva konturer som sedan tidigare utvecklats på FOI. Beräkningsbördan för den nya metoden är endast en bråkdel av den förra, samtidigt som prestandan, särskilt i urbana miljöer, har kunnat förbättras.</p><p>De segmenteringsmetoder som introducerats har visat på lovande resultat vad gäller möjligheten att särskilja olika typer av objekt. Slutligen har en ny uppsättning deskriptorer och beslutsvärden till den objektbaserade klassificeraren föreslagits. Den har enligt de tester som presenteras i rapporten visats sig vara mer effektiv än den uppsättning som använts fram till idag.</p>