In this dissertation, novel variational optical-flow and active-contour methods are investigated to address challenging problems in computer vision and shape-based imaging. Starting from traditional applications of these methods in computer vision, such as object segmentation, tracking, and detection, this research subsequently applies similar active contour techniques to the realm of shape-based imaging, which is an image reconstruction technique estimating object shapes directly from physical wave measurements. In particular, the first and second part of this thesis deal with the following two physically inspired computer vision applications. Optical Flow for Vision-Based Flame Detection: Fire motion is estimated using optimal mass transport optical flow, whose motion model is inspired by the physical law of mass conservation, a governing equation for fire dynamics. The estimated motion fields are used to first detect candidate regions characterized by high motion activity, which are then tracked over time using active contours. To classify candidate regions, a neural net is trained on a set of novel motion features, which are extracted from optical flow fields of candidate regions. Coupled Photo-Geometric Object Features: Active contour models for segmentation in thermal videos are presented, which generalize the well-known Mumford-Shah functional. The diffusive nature of heat processes in thermal imagery motivates the use of Mumford-Shah-type smooth approximations for the image radiance. Mumford-Shah's isotropic smoothness constraint is generalized to anisotropic diffusion in this dissertation, where the image gradient is decomposed into components parallel and perpendicular to level set curves describing the object's boundary contour. In a limiting case, this anisotropic Mumford-Shah segmentation energy yields a one-dimensional ``photo-geometric'' representation of an object which is invariant to translation, rotation and scale. These properties allow the photo-geometric object representation to be efficiently used as a radiance feature; a recognition-segmentation active contour energy, whose shape and radiance follow a training model obtained by principal component analysis of a training set's shape and radiance features, is finally applied to tracking problems in thermal imagery. The third part of this thesis investigates a physics-driven active contour approach for shape-based imaging. Adjoint Active Contours for Shape-Based Imaging: The goal of this research is to estimate both location and shape of buried objects from surface measurements of waves scattered from the object. These objects' shapes are described by active contours: A misfit energy quantifying the discrepancy between measured and simulated wave amplitudes is minimized with respect to object shape using the adjoint state method. The minimizing active contour evolution requires numerical forward scattering solutions, which are obtained by way of the method of fundamental solutions, a meshfree collocation method. In combination with active contours being implemented as level sets, one obtains a completely meshfree algorithm; a considerable advantage over previous work in this field. With future applications in medical and geophysical imaging in mind, the method is formulated for acoustic and elastodynamic wave processes in the frequency domain.

Objective and accurate surface measurements are important in many clinical disciplines. Non-irradiating and low cost alternatives are available but validation of these measurement tools for clinical application is variable and sparse. This thesis presents a three dimensional (3D) surface measurement method validated by gold standard Computed Tomography (CT). Forty-one 3D surface data sets were acquired by two modalities, a laser scanner and a binocular camera. The binocular camera was tested with three different texture modifiers that increased the colour variability of the imaged surface. A surface area calculation algorithm was created to process the data sets. Relative differences were calculated for each area measurement with respect to its corresponding CT measurement. The laser scanner data sets were affected by movement and specular reflection artefacts. The measurements were statistically equivalent to CT if less than 20% error were considered acceptable. The binocular camera with the slide projected texture modifier was shown to be statistically equivalent to CT gold standard with less than 5% error (p < 0.0005). The surface area measurement method can easily be expanded and customized. By following the protocol outlined by the example in this work, researchers and clinicians would also be able to objectively asses other vision systems' performance and suitability. / Thesis (Master, Computing) -- Queen's University, 2012-01-10 11:37:50.374

Gossamer membranes are large, ultra light weight, highly flexible thin films. They have been proposed for use as elements in systems such as solar sails and optical apertures, whose large areas require a low-mass material that can be launched in a compact package and then deployed to operational configuration upon reaching orbit. Many of the proposed applications require that the film possess a flat, wrinkle-free surface. Surface wrinkle configuration is determined, in part, by the method used to support the film. One configuration that has not been studied in detail involves the formation of vertical wrinkles oriented along the direction of a tensile force applied at the upper and lower horizontal film supports. An experiment was designed to allow known forces to be applied to a 9 inch by 9 inch square sample of film supported at its upper and lower boundaries. Four films 7.6 m and 12.7 m thick samples of Kapton (polymide), and 12.2 m and 23.4 m thick samples of Mylar were loaded at levels of applied tensile force ranging from 1.446 to 4.388 N. The out-of-plane surface contours that resulted were measured using close-range photogrammetry, a non-contact, optical measurement technique. Experimental results indicate that both wrinkle wavelength and amplitude decrease as a function of applied force magnitude. These trends matched those obtained using numerical techniques, which also showed that lateral border strain, not measured during the experiment, may be a more important factor in determining surface wrinkle configuration. After presentation of the results, the photogrammetry technique is further considered as a tool for use in the manufacturing industry, in similar close-range applications, for the measurement of both dimensions and displacements.

Thesis (M.S.)--University of Texas at El Paso, 2007. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

La Tomographie Calculée (CT) est une technique non-invasive permettant de fournir des images de toutes les parties du corps humain sans superposition des structures adjacentes. Cette technique se base sur l'absorption de rayon X et permet la reconstruction d'images du corps humain. Les mesures avec CT à rayons X sont soumises à de nombreuses imperfections ou d'artefacts d'images qui comportent : bruit quantique, diffusion des rayons X par le patient, et des effets non linéaires de volume. Le traitement d'image est un outil indispensable pour améliorer le contraste et extraire d'une manière automatique les régions d'intérêts. L'analyse des données d'images CT est une aide à la décision pour l'apparition d'un cancer en phase naissante. La segmentation automatique de la tomographie calculée (CT) est une étape importante pour la chirurgie assistée qui requière à la fois une grande précision et une interaction minimale de l'utilisateur. Les tentatives d'utilisations de la segmentation, comprenant le seuillage (global et optimal), le filtrage, la segmentation par région de type watershead, et l'approche basée sur les contours actifs, ne sont pas pleinement satisfaisantes. Dans cette thèse, nous nous intéressons aux techniques d'extraction automatique des régions représentant les zones cancéreuses dans des images obtenues par la CT. Un nouvel algorithme basé sur la programmation dynamique, est proposé pour l'ajustement automatique des paramètres des contours actifs. Dans notre nouvelle approche, nous utilisons l'entropie pour l'estimation des paramètres alpha et beta de l'énergie interne. Pour obtenir des images pour l'identification des régions malignes, qui soient de meilleure qualité en terme de contraste, nous avons utilisé la fusion d'images à partir de la Transformée en ondelettes. Toutes ces méthodes ont été implémentées sous forme de plugins dans le logiciel GIMP. / Computed Tomography (CT) is a non-invasive technique which provides images of the human body without superposing adjacent structures. This technique is based on the absorption of X-rays by the human body. Analysis from X-ray absorption is subject to a variety of imperfections and image artifacts including quantum noise, X-rays scattered by the patient (absorptive environment), beam hardening, and nonlinear volume effects. Image processing is a crucial tool for contrast enhancement and region analysis. Analysis of CT images is a decision-making tool for cancer formation at an incipient phase. Segmentation of computed tomography (CT) images is an important step in image-guided surgery that requires both high accuracy and minimal user interaction. Previous attempts include thresholding (global and optimal), region growing (region competition, watershed segmentation), edge tracing, and parametric active contour (AC) approaches for segmentation, are not fully satisfying. In this dissertation we have been interested in the CT image processing methods to detect and analyze cancerous regions in phase II and III. A new algorithm, which hinges on dynamic programming, has been proposed for automatically extracting region of interest using adapted active contours. In our new approach, Entropy is used to estimate the parameters alpha and beta of the active contour internal energy. In order to enhance the image quality in terms of contrast and to understand more the regions of interest, image fusion is used. Image fusion is a process of combining multiple images into a single image containing more relevant information. We use Wavelet Transform and a specific Fusion Rule to identify and select relevant information of the process. All these methods have been implemented as plugins in GIMP software.

Les aides à la conduite sont des systèmes qui aident le conducteur à mieux appréhender la tâche de conduite en situation difficile. Parmi les différents capteurs qu'utilisent ces ADAS, des caméras sont embarquées et délivrent des images de la scène routière qui sont traitées et analysées de manière à informer le conducteur des dangers éventuels ou enclencher des systèmes d'urgence. Les caméras issues de ces ADAS capturent l'environnement routier d'une manière qui est loin d'être représentative de la perception qu'aurait un conducteur. Une des conséquences éventuelles est que ces ADAS soient contre-productives en déclenchant inopinément des systèmes d'alerte et d'action à l'encontre du conducteur. De manière à remplir complétement la vocation de ces ADAS, il est primordial de disposer d'une carte de la perception de l'environnement routier du point de vue du conducteur de manière à ajuster l'aide dont il pourrait avoir besoin. Nous proposons d'estimer par traitement d'image, la visibilité routière du point de vue du conducteur en utilisant un algorithme bio-inspiré simulant la sensibilité au contraste de l'œil humain. Dans un premier temps, nous étendons un modèle de CSF (Contrast Sensitivity Function) de manière à prendre en compte des taux de détection cohérents avec la sécurité routière, l'orientation, la couleur et l'âge du conducteur. Dans un second temps, nous modélisons notre modèle de CSF par un filtrage spatial et en calculons la visibilité en chaque pixel de l'image. Nous appliquons cette carte de visibilité sur une carte de contours issue de notre détecteur de contour bio-inspiré. Ainsi, nous considérons les contours des objets routiers présents dans l'image plutôt que leurs caractéristiques de manière à éviter toute hypothèse. Ces contours sont associés à un niveau de visibilité indiquant s'ils sont visibles ou pas par l'observateur. Nous validons le procédé en le comparant à des performances visuelles d'observateurs, en condition de laboratoire, pour une détection de cible et en situation de conduite simulée en conduite de nuit. Dans un deuxième temps, nous associons ces niveaux de visibilité en deux unités facilement compréhensibles pour des ADAS: un temps de réaction et une distance perçue. En premier lieu, nous proposons un modèle d'estimation du temps de perception du conducteur en fonction de la visibilité en nous inspirant de la loi de Piéron sur des données expérimentales de détection de cibles sur des images routières de synthèse pour une certaine densité de brouillard de jour. Les études ont montré que les conducteurs auraient tendance à se rapprocher du véhicule devant eux de manière à ne pas les perdre de vue. Ce constat nous renseigne sur le fait que le conducteur ne dispose pas suffisamment de visibilité à ses yeux dans cette configuration de conduite. Nous montrons l'intérêt des méthodes de restauration d'images en termes de gain de temps de réaction et de performance visuelle comme le taux de détection du véhicule devant lui. Dans un second temps, nous estimons une distance par rapport au véhicule précédent du point de vue du conducteur en nous inspirant de la détection des feux arrière du véhicule situé devant le conducteur. Les résultats ont montré que les conducteurs estimaient mal les distances sur obstacles lointains en comparaison des aides à la conduite basées sur des imageurs optique, radar ou lidar pour une conduite de nuit. D'après ce constat, les ADAS jouent un rôle fondamental pour prévenir le conducteur de sa conduite inadaptée. Enfin, nous délimitons les limites de nos modèles de CSF et de visibilité et proposons plusieurs perspectives. Pour des applications routières, une des perspectives qui a été concrétisée partiellement est l'évaluation objective des systèmes d'éclairage par notre modèle de visibilité et sa cohérence avec une expertise subjective / The driver assistance systems are systems that help the driver to better understand the plight driving task. Among the various sensors used by these ADAS, cameras are shipped and deliver images of the road scene which are processed and analyzed to inform the driver of potential hazards or switch of emergency systems. The cameras capture from these ADAS is far from representative of perception would have a driver. One of the possible consequences is that these ADAS can be counter productive in triggering warning and action against the driver. In order to completely fulfill the objectives of such ADAS, it is essential to have a map of the perception of the road environment from the perspective of the driver to adjust the help they might need. We propose to estimate by image processing, road visibility from the driver's perspective using a bio-inspired algorithm simulating the contrast sensitivity of the human eye. First, we extend a model of CSF (Contrast Sensitivity Function) to consider coherent detection rate with road safety, orientation, color and age of the driver. In a second step, we model our CSF spatial filtering and calculate the visibility for each pixel of the image. We apply this visibility map on a map of contours of our bio-inspired edge detector. Thus, we consider the contours of the road objects in the image rather than the characteristics in order to avoid assumptions. These contours are associated with a level of visibility as to whether or not they are visible by the observer. We validate the method by comparing it with the visual performance of observers in laboratory conditions for target detection and simulated driving situation in night driving. Secondly, we combine these two levels of visibility in easily understandable units for ADAS: a reaction time and a target distance. First, we propose a model to estimate the driver's reaction time depending on the visibility (inspired by Piéron's law of target detection) with experimental data on road synthetic images for some daylight fog density. Studies have shown that drivers would tend toget closer to the vehicle in front of them in order not to lose sight of them. This observation tells us that the driver does not have enough visibility in that configuration. We show the interest of the image restoration methods in terms of reaction time and gain in visual performance as well as vehicle detection rate. In a second step, we estimate a distance from the point of view of the driver taking inspiration from the detection of the rear lights of the vehicle in front of the driver. The results showed that drivers were bad about the distance evaluation of distant obstacles compared to driving aids based on optical imaging, radar or lidar for night driving. Based on this observation, the ADAS may play a fundamental role in preventing the driver from his inappropriate behavior. Finally, we outline the limits of our models CSF and visibility and offer several perspectives for road applications, one of which was the objective evaluation of lighting systems by our model of visibility and consistency with a subjective expertise

No description available.

The human visual system has the remarkable capacity to transform spatio-temporal patterns of light into structured units of perception. Much research has focused on how the visual system integrates information around the perimeter of closed contours to form the perception of shape. This dissertation extends previous work by investigating how the perception of curvature along closed-contour shapes is affected by the presence of additional shapes that appear close to the target shape in space and/or time. Chapter 2 examined the ability of shape mechanisms at representing low frequency curvature in the presence of a higher frequency component along contours in multi-shape displays. We found that additions of high amplitude, high frequency curvature along a contour path can modulate the strength of interaction observed between shapes, and thus attenuates the contribution of low frequency components in interactions between neighbouring contours. Chapter 3 examined what curvature features are of importance in modulating phase dependent interactions between shapes. Results revealed that phase-dependent masking does not depend on curvature frequency, but is related to sensitivity for phase shifts in isolated contours, and is affected by both positive and negative curvature extrema. Computational simulations aimed at modelling the population responses evoked in intermediate shape processing areas (i.e., V4) suggest sensitivity to shifts in phase of shapes is not well captured by such a population code, and therefore alternative explanations are required. Chapter 4 examined how sensitivity to curvature deformations along the contour of a closed shape changes as a function of polar angle, angular frequency, and spatial uncertainty. Results show that human observers are, at first approximation, uniformly sensitivity to curvature deformations across all polar angles tested, and this result holds despite changes in angular frequency and spatial uncertainty. Chapter 5 examined whether the strength of spatial masking between shapes is affected by the presentation of a temporal mask. Our results demonstrate that a temporal mask affected spatial masking only when it preceded the target-mask stimulus by 130-180ms. Furthermore, the effects of a temporal mask on spatial masking are approximately additive, suggesting that separate components contribute to spatial and temporal interactions between shapes. / Thesis / Doctor of Philosophy (PhD)

Contours can be understood as the shape or format of an object. In Music contour can represent a parameter in function of another, like pitch in function of density or density in function of amplitude. Contours are important because, as well as pitch sets and motives, they can help giving coherence to a musical piece.Theories of contours have been used in areas such as Ear Training and Analysis, but the systematic use of contours for generation of compositional material is an issue still lacking literature.In this thesis I present the piece "Em torno da romã" [Around the pomegranate] and its analysis. This piece, for woodwind quintet, was composed using combinations of contour operations associated with parameters such as pitch, tempo, density and texture. In order to accomplish this task, I did a literature review of contour theories, I did a mapping of contours to musical elements, I composed studies of possibilities for experimentation with contours, I develop the Goiaba, a software to assist in processing contours for composition, and finally composed the piece "Em torno da romã".This study helps to advance the state of art of contour theories through composition contour operations experiments using contour operations and contributes with new tools to the composition field.My conclusion is that contours can be used in a systematic way in musical composition, but we still need further study. Thus this depth and continuity in development of Goiaba are possible future activities resulting from this work.

The purpose of the present study was to investigate the role of pitch contours in directing infant attention to adult speech. Several studies have shown that infants from a few days old to 9 months of age prefer infant-directed (ID) over adult-directed (AD) speech. Moreover, 4-month-olds have been shown to prefer pitch contours that simulate ID speech, suggesting that the exaggerated pitch contours are necessary for infant attention. The current study investigated this attentional preference utilizing ID and AD pitch contours in a fixation-based preference procedure. Results from the first experiment failed to show a similar preference for the ID pitch contours. Because a lack of preference could have been due to a failure to discriminate, a habituation study was also conducted. The results from the second experiment showed that 4-month-olds can discriminate the ID and AD pitch contours. From these results, it is argued that the pitch contour may be but one of many possible prosodic characteristics that attract infant attention and this attention may occur only within a language context. It is suggested that future studies investigate ID speech using a more context-dependent procedure, where natural or more complete speech samples are utilized. / Master of Science